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--- |
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license: llama3.1 |
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base_model: meta-llama/Meta-Llama-3.1-8B |
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tags: |
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- generated_from_trainer |
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datasets: |
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- cognitivecomputations/Dolphin-2.9 |
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- m-a-p/CodeFeedback-Filtered-Instruction |
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- cognitivecomputations/dolphin-coder |
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- cognitivecomputations/samantha-data |
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- microsoft/orca-math-word-problems-200k |
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- mlabonne/FineTome-100k |
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- arcee/agent_data |
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- PawanKrd/math-gpt-4o-200k |
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- cognitivecomputations/SystemChat-2.0 |
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--- |
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# Dolphin 2.9.4 Llama 3.1 8b 🐬 |
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This is the GGUF conversion, for use with llama.cpp, ollama, lmstudio etc. |
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Curated and trained by Eric Hartford and Cognitive Computations |
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[](https://discord.gg/h3K4XGj2RH) |
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Discord: https://discord.gg/h3K4XGj2RH |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/ldkN1J0WIDQwU4vutGYiD.png" width="600" /> |
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Our appreciation for the sponsors of Dolphin 2.9.4: |
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- [Crusoe Cloud](https://crusoe.ai/) - provided excellent on-demand 8xL40S node |
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This model is based on Meta Llama 3.1 8b, and is governed by the Llama 3.1 license. |
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The base model has 128K context, and our finetuning used 8192 sequence length. |
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Dolphin 2.9.4 uses ChatML prompt template format. |
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example: |
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``` |
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<|im_start|>system |
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You are Dolphin, a helpful AI assistant.<|im_end|> |
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<|im_start|>user |
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{prompt}<|im_end|> |
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<|im_start|>assistant |
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``` |
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Dolphin-2.9.4 has a variety of instruction following, conversational, and coding skills. It also has agentic abilities and supports function calling. |
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It is especially trained to obey the system prompt, and follow instructions in many languages. |
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Dolphin is uncensored. We have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant with any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly. |
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<details><summary>Evals</summary> |
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``` |
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hf (pretrained=/workspace/axolotl/dolphin-2.9.4-llama3.1-8b-hf,dtype=bfloat16), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: auto (4) |
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| Tasks |Version|Filter|n-shot| Metric | |Value | |Stderr| |
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|-----------------------------------------------------------|-------|------|-----:|-----------------------|---|-----:|---|------| |
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|leaderboard |N/A |none | 0|acc |↑ |0.2926|± |0.0041| |
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| | |none | 0|acc_norm |↑ |0.4513|± |0.0053| |
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| | |none | 0|exact_match |↑ |0.0982|± |0.0079| |
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| | |none | 0|inst_level_loose_acc |↑ |0.3825|± |N/A | |
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| | |none | 0|inst_level_strict_acc |↑ |0.3597|± |N/A | |
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| | |none | 0|prompt_level_loose_acc |↑ |0.2421|± |0.0184| |
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| | |none | 0|prompt_level_strict_acc|↑ |0.2181|± |0.0178| |
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| - leaderboard_bbh |N/A |none | 3|acc_norm |↑ |0.4931|± |0.0061| |
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| - leaderboard_bbh_boolean_expressions | 0|none | 3|acc_norm |↑ |0.8000|± |0.0253| |
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| - leaderboard_bbh_causal_judgement | 0|none | 3|acc_norm |↑ |0.5615|± |0.0364| |
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| - leaderboard_bbh_date_understanding | 0|none | 3|acc_norm |↑ |0.4520|± |0.0315| |
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| - leaderboard_bbh_disambiguation_qa | 0|none | 3|acc_norm |↑ |0.6640|± |0.0299| |
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| - leaderboard_bbh_formal_fallacies | 0|none | 3|acc_norm |↑ |0.5600|± |0.0315| |
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| - leaderboard_bbh_geometric_shapes | 0|none | 3|acc_norm |↑ |0.3640|± |0.0305| |
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| - leaderboard_bbh_hyperbaton | 0|none | 3|acc_norm |↑ |0.6320|± |0.0306| |
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| - leaderboard_bbh_logical_deduction_five_objects | 0|none | 3|acc_norm |↑ |0.4600|± |0.0316| |
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| - leaderboard_bbh_logical_deduction_seven_objects | 0|none | 3|acc_norm |↑ |0.4360|± |0.0314| |
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| - leaderboard_bbh_logical_deduction_three_objects | 0|none | 3|acc_norm |↑ |0.6160|± |0.0308| |
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| - leaderboard_bbh_movie_recommendation | 0|none | 3|acc_norm |↑ |0.7880|± |0.0259| |
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| - leaderboard_bbh_navigate | 0|none | 3|acc_norm |↑ |0.5200|± |0.0317| |
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| - leaderboard_bbh_object_counting | 0|none | 3|acc_norm |↑ |0.4520|± |0.0315| |
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| - leaderboard_bbh_penguins_in_a_table | 0|none | 3|acc_norm |↑ |0.5205|± |0.0415| |
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| - leaderboard_bbh_reasoning_about_colored_objects | 0|none | 3|acc_norm |↑ |0.5120|± |0.0317| |
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| - leaderboard_bbh_ruin_names | 0|none | 3|acc_norm |↑ |0.6320|± |0.0306| |
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| - leaderboard_bbh_salient_translation_error_detection | 0|none | 3|acc_norm |↑ |0.4320|± |0.0314| |
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| - leaderboard_bbh_snarks | 0|none | 3|acc_norm |↑ |0.5843|± |0.0370| |
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| - leaderboard_bbh_sports_understanding | 0|none | 3|acc_norm |↑ |0.7040|± |0.0289| |
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| - leaderboard_bbh_temporal_sequences | 0|none | 3|acc_norm |↑ |0.1440|± |0.0222| |
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| - leaderboard_bbh_tracking_shuffled_objects_five_objects | 0|none | 3|acc_norm |↑ |0.1560|± |0.0230| |
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| - leaderboard_bbh_tracking_shuffled_objects_seven_objects| 0|none | 3|acc_norm |↑ |0.1320|± |0.0215| |
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| - leaderboard_bbh_tracking_shuffled_objects_three_objects| 0|none | 3|acc_norm |↑ |0.2840|± |0.0286| |
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| - leaderboard_bbh_web_of_lies | 0|none | 3|acc_norm |↑ |0.4840|± |0.0317| |
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| - leaderboard_gpqa |N/A |none | 0|acc_norm |↑ |0.2903|± |0.0132| |
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| - leaderboard_gpqa_diamond | 1|none | 0|acc_norm |↑ |0.2980|± |0.0326| |
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| - leaderboard_gpqa_extended | 1|none | 0|acc_norm |↑ |0.2839|± |0.0193| |
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| - leaderboard_gpqa_main | 1|none | 0|acc_norm |↑ |0.2946|± |0.0216| |
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| - leaderboard_ifeval | 2|none | 0|inst_level_loose_acc |↑ |0.3825|± |N/A | |
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| | |none | 0|inst_level_strict_acc |↑ |0.3597|± |N/A | |
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| | |none | 0|prompt_level_loose_acc |↑ |0.2421|± |0.0184| |
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| | |none | 0|prompt_level_strict_acc|↑ |0.2181|± |0.0178| |
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| - leaderboard_math_algebra_hard | 1|none | 4|exact_match |↑ |0.1596|± |0.0209| |
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| - leaderboard_math_counting_and_prob_hard | 1|none | 4|exact_match |↑ |0.0488|± |0.0195| |
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| - leaderboard_math_geometry_hard | 1|none | 4|exact_match |↑ |0.0530|± |0.0196| |
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| - leaderboard_math_hard |N/A |none | 4|exact_match |↑ |0.0982|± |0.0079| |
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| - leaderboard_math_intermediate_algebra_hard | 1|none | 4|exact_match |↑ |0.0143|± |0.0071| |
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| - leaderboard_math_num_theory_hard | 1|none | 4|exact_match |↑ |0.0455|± |0.0168| |
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| - leaderboard_math_prealgebra_hard | 1|none | 4|exact_match |↑ |0.2591|± |0.0316| |
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| - leaderboard_math_precalculus_hard | 1|none | 4|exact_match |↑ |0.0519|± |0.0192| |
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| - leaderboard_mmlu_pro | 0.1|none | 5|acc |↑ |0.2926|± |0.0041| |
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| - leaderboard_musr |N/A |none | 0|acc_norm |↑ |0.3862|± |0.0173| |
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| - leaderboard_musr_murder_mysteries | 1|none | 0|acc_norm |↑ |0.5280|± |0.0316| |
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| - leaderboard_musr_object_placements | 1|none | 0|acc_norm |↑ |0.3594|± |0.0300| |
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| - leaderboard_musr_team_allocation | 1|none | 0|acc_norm |↑ |0.2720|± |0.0282| |
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| Groups |Version|Filter|n-shot| Metric | |Value | |Stderr| |
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|------------------------|-------|------|-----:|-----------------------|---|-----:|---|------| |
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|leaderboard |N/A |none | 0|acc |↑ |0.2926|± |0.0041| |
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| | |none | 0|acc_norm |↑ |0.4513|± |0.0053| |
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| | |none | 0|exact_match |↑ |0.0982|± |0.0079| |
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| | |none | 0|inst_level_loose_acc |↑ |0.3825|± |N/A | |
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| | |none | 0|inst_level_strict_acc |↑ |0.3597|± |N/A | |
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| | |none | 0|prompt_level_loose_acc |↑ |0.2421|± |0.0184| |
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| | |none | 0|prompt_level_strict_acc|↑ |0.2181|± |0.0178| |
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| - leaderboard_bbh |N/A |none | 3|acc_norm |↑ |0.4931|± |0.0061| |
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| - leaderboard_gpqa |N/A |none | 0|acc_norm |↑ |0.2903|± |0.0132| |
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| - leaderboard_math_hard|N/A |none | 4|exact_match |↑ |0.0982|± |0.0079| |
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| - leaderboard_musr |N/A |none | 0|acc_norm |↑ |0.3862|± |0.0173| |
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``` |
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</details> |
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[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.1` |
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```yaml |
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base_model: meta-llama/Meta-Llama-3.1-8B |
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model_type: LlamaForCausalLM |
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tokenizer_type: AutoTokenizer |
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load_in_8bit: false |
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# load_in_4bit: true |
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strict: false |
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datasets: |
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- path: /workspace/datasets/dolphin-2.9.4/dolphin201-sharegpt2.jsonl |
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type: sharegpt |
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conversation: chatml |
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chat_template: chatml |
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# adapter: qlora |
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# lora_r: 128 |
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# lora_alpha: 16 |
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# lora_modules_to_save: [embed_tokens, lm_head] |
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# lora_dropout: 0.05 |
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# lora_target_linear: true |
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unfrozen_parameters: |
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- input_layernorm |
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- model.norm |
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- post_attention_layernorm |
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- self_attn.rotary_emb |
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- ^lm_head.weight$ |
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- ^model.embed_tokens.weight$ |
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# mlp.down_proj layers |
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- model.layers.1.mlp.down_proj |
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- model.layers.0.mlp.down_proj |
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- model.layers.30.mlp.down_proj |
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- model.layers.2.mlp.down_proj |
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- model.layers.21.mlp.down_proj |
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- model.layers.22.mlp.down_proj |
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- model.layers.29.mlp.down_proj |
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- model.layers.5.mlp.down_proj |
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- model.layers.4.mlp.down_proj |
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- model.layers.20.mlp.down_proj |
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- model.layers.23.mlp.down_proj |
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- model.layers.19.mlp.down_proj |
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- model.layers.3.mlp.down_proj |
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- model.layers.17.mlp.down_proj |
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- model.layers.6.mlp.down_proj |
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- model.layers.31.mlp.down_proj |
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# mlp.up_proj layers |
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- model.layers.4.mlp.up_proj |
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- model.layers.3.mlp.up_proj |
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- model.layers.0.mlp.up_proj |
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- model.layers.5.mlp.up_proj |
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- model.layers.7.mlp.up_proj |
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- model.layers.6.mlp.up_proj |
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- model.layers.2.mlp.up_proj |
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- model.layers.1.mlp.up_proj |
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- model.layers.8.mlp.up_proj |
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- model.layers.12.mlp.up_proj |
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- model.layers.14.mlp.up_proj |
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- model.layers.9.mlp.up_proj |
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- model.layers.15.mlp.up_proj |
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- model.layers.17.mlp.up_proj |
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- model.layers.13.mlp.up_proj |
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- model.layers.19.mlp.up_proj |
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# self_attn.k_proj layers |
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- model.layers.29.self_attn.k_proj |
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- model.layers.25.self_attn.k_proj |
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- model.layers.23.self_attn.k_proj |
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- model.layers.28.self_attn.k_proj |
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- model.layers.21.self_attn.k_proj |
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- model.layers.19.self_attn.k_proj |
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- model.layers.22.self_attn.k_proj |
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- model.layers.20.self_attn.k_proj |
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- model.layers.24.self_attn.k_proj |
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- model.layers.31.self_attn.k_proj |
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- model.layers.27.self_attn.k_proj |
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- model.layers.26.self_attn.k_proj |
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- model.layers.17.self_attn.k_proj |
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- model.layers.11.self_attn.k_proj |
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- model.layers.18.self_attn.k_proj |
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- model.layers.14.self_attn.k_proj |
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# self_attn.o_proj layers |
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- model.layers.14.self_attn.o_proj |
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- model.layers.7.self_attn.o_proj |
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- model.layers.5.self_attn.o_proj |
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- model.layers.11.self_attn.o_proj |
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- model.layers.6.self_attn.o_proj |
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- model.layers.24.self_attn.o_proj |
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- model.layers.9.self_attn.o_proj |
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- model.layers.13.self_attn.o_proj |
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- model.layers.10.self_attn.o_proj |
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- model.layers.12.self_attn.o_proj |
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- model.layers.8.self_attn.o_proj |
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- model.layers.25.self_attn.o_proj |
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- model.layers.21.self_attn.o_proj |
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- model.layers.23.self_attn.o_proj |
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- model.layers.15.self_attn.o_proj |
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- model.layers.16.self_attn.o_proj |
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# self_attn.q_proj layers |
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- model.layers.8.self_attn.q_proj |
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- model.layers.13.self_attn.q_proj |
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- model.layers.9.self_attn.q_proj |
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- model.layers.14.self_attn.q_proj |
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- model.layers.10.self_attn.q_proj |
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- model.layers.11.self_attn.q_proj |
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- model.layers.0.self_attn.q_proj |
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- model.layers.15.self_attn.q_proj |
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- model.layers.1.self_attn.q_proj |
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- model.layers.6.self_attn.q_proj |
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- model.layers.5.self_attn.q_proj |
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- model.layers.7.self_attn.q_proj |
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- model.layers.12.self_attn.q_proj |
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- model.layers.16.self_attn.q_proj |
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- model.layers.17.self_attn.q_proj |
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- model.layers.26.self_attn.q_proj |
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# self_attn.v_proj layers |
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- model.layers.26.self_attn.v_proj |
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- model.layers.17.self_attn.v_proj |
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- model.layers.3.self_attn.v_proj |
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- model.layers.28.self_attn.v_proj |
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- model.layers.29.self_attn.v_proj |
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- model.layers.21.self_attn.v_proj |
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- model.layers.15.self_attn.v_proj |
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- model.layers.16.self_attn.v_proj |
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- model.layers.20.self_attn.v_proj |
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- model.layers.25.self_attn.v_proj |
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- model.layers.6.self_attn.v_proj |
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- model.layers.23.self_attn.v_proj |
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- model.layers.4.self_attn.v_proj |
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- model.layers.1.self_attn.v_proj |
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- model.layers.22.self_attn.v_proj |
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- model.layers.14.self_attn.v_proj |
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# mlp.gate_proj layers |
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- model.layers.1.mlp.gate_proj |
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- model.layers.2.mlp.gate_proj |
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- model.layers.3.mlp.gate_proj |
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- model.layers.4.mlp.gate_proj |
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- model.layers.0.mlp.gate_proj |
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- model.layers.25.mlp.gate_proj |
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- model.layers.26.mlp.gate_proj |
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- model.layers.5.mlp.gate_proj |
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- model.layers.24.mlp.gate_proj |
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- model.layers.28.mlp.gate_proj |
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- model.layers.23.mlp.gate_proj |
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- model.layers.27.mlp.gate_proj |
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- model.layers.21.mlp.gate_proj |
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- model.layers.22.mlp.gate_proj |
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- model.layers.29.mlp.gate_proj |
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- model.layers.20.mlp.gate_proj |
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dataset_prepared_path: /workspace/axolotl/dolph-2.9.4-nemo-prepared |
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val_set_size: 0.01 |
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output_dir: /workspace/axolotl/dolphin-2.9.4-llama3.1-8b |
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sequence_len: 8192 |
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sample_packing: true |
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pad_to_sequence_len: true |
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wandb_project: dolphin-2.9.4-llama3.1-8b |
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wandb_watch: |
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wandb_run_id: |
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wandb_log_model: |
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gradient_accumulation_steps: 16 |
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micro_batch_size: 2 |
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num_epochs: 3 |
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optimizer: adamw_torch |
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lr_scheduler: cosine |
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learning_rate: 5e-6 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: |
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gradient_checkpointing: true |
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gradient_checkpointing_kwargs: |
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use_reentrant: false |
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early_stopping_patience: |
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resume_from_checkpoint: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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warmup_steps: 100 |
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# evals_per_epoch: 4 |
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eval_table_size: |
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saves_per_epoch: 1 |
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save_total_limit: 2 |
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save_steps: |
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debug: |
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deepspeed: deepspeed_configs/zero3_bf16.json |
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weight_decay: 0.1 |
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special_tokens: |
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eos_token: "<|im_end|>" |
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bos_token: "<|begin_of_text|>" |
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pad_token: "<|finetune_right_pad_id|>" |
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tokens: |
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- "<|im_start|>" |
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# fsdp: |
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# - full_shard |
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# - auto_wrap |
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# fsdp_config: |
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# fsdp_limit_all_gathers: true |
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# fsdp_sync_module_states: true |
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# fsdp_offload_params: true |
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# fsdp_use_orig_params: false |
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# fsdp_cpu_ram_efficient_loading: true |
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# fsdp_transformer_layer_cls_to_wrap: MixtralSparseMoeBlock |
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# fsdp_state_dict_type: FULL_STATE_DICT |
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# fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP |
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# fsdp_sharding_strategy: FULL_SHARD |
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# fsdp_forward_prefetch: false |
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# fsdp_backward_prefetch: BACKWARD_PRE |
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``` |
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</details><br> |
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# workspace/axolotl/dolphin-2.9.4-llama3.1-8b |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B](https://huggingface.co./meta-llama/Meta-Llama-3.1-8B) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5655 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-06 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 256 |
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- total_eval_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.5837 | 1.0180 | 1161 | 0.5814 | |
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| 0.5525 | 2.0179 | 2322 | 0.5671 | |
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| 0.5514 | 2.9624 | 3420 | 0.5655 | |
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### Framework versions |
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|
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- Transformers 4.44.0.dev0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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