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--- |
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base_model: Qwen/Qwen2-7B |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: workspace/data/outputs/Qwen2-7B-TestInstructFinetune-LORA |
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results: [] |
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--- |
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If I thought I had no idea what I was doing with quantization, I REALLY have no idea what I’m doing with LORA Fine Tuning... This is my terrible attempt to instruct tune base Qwen2-7B, i haven't even tested this yet, i'll do that eventually... |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/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: /workspace/data/models/Qwen2-7B |
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model_type: Qwen2ForCausalLM |
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tokenizer_type: Qwen2Tokenizer |
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trust_remote_code: true |
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load_in_8bit: false |
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load_in_4bit: false |
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strict: false |
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datasets: |
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# - path: NobodyExistsOnTheInternet/ToxicQAFinal |
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# type: sharegpt |
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# - path: /workspace/data/SystemChat_filtered_sharegpt.jsonl |
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# type: sharegpt |
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# conversation: chatml |
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- path: /workspace/data/Opus_Instruct-v2-6.5K-Filtered-v2.json |
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type: |
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field_system: system |
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field_instruction: prompt |
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field_output: response |
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format: "[INST] {instruction} [/INST]" |
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no_input_format: "[INST] {instruction} [/INST]" |
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# - path: Undi95/orthogonal-activation-steering-TOXIC |
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# type: |
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# field_instruction: goal |
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# field_output: target |
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# format: "[INST] {instruction} [/INST]" |
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# no_input_format: "[INST] {instruction} [/INST]" |
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# split: test |
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- path: cognitivecomputations/WizardLM_alpaca_evol_instruct_70k_unfiltered |
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type: alpaca |
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split: train |
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dataset_prepared_path: /workspace/data/last_run_prepared |
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val_set_size: 0.15 |
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output_dir: /workspace/data/outputs/Qwen2-7B-TestInstructFinetune-LORA |
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chat_template: chatml |
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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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adapter: lora |
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lora_model_dir: |
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lora_r: 32 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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wandb_project: |
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wandb_entity: |
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wandb_watch: |
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wandb_name: |
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wandb_log_model: |
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gradient_accumulation_steps: 8 |
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micro_batch_size: 1 |
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num_epochs: 4 |
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optimizer: adamw_torch |
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lr_scheduler: cosine |
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learning_rate: 3e-5 |
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train_on_inputs: false |
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group_by_length: true |
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bf16: true |
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fp16: false |
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tf32: false |
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gradient_checkpointing: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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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: 10 |
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evals_per_epoch: 4 |
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eval_table_size: |
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saves_per_epoch: 4 |
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debug: |
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deepspeed: |
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weight_decay: 0.05 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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pad_token: "<|endoftext|>" |
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eos_token: "<|im_end|>" |
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``` |
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</details><br> |
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# workspace/data/outputs/Qwen2-7B-TestInstructFinetune-LORA |
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This model was trained from scratch on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5037 |
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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: 3e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 8 |
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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: 10 |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.6232 | 0.0027 | 1 | 0.6296 | |
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| 0.5602 | 0.2499 | 91 | 0.5246 | |
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| 0.4773 | 0.4998 | 182 | 0.5155 | |
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| 0.4375 | 0.7497 | 273 | 0.5116 | |
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| 0.6325 | 0.9997 | 364 | 0.5092 | |
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| 0.4385 | 1.2382 | 455 | 0.5073 | |
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| 0.4949 | 1.4882 | 546 | 0.5061 | |
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| 0.503 | 1.7381 | 637 | 0.5052 | |
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| 0.5023 | 1.9880 | 728 | 0.5046 | |
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| 0.3737 | 2.2238 | 819 | 0.5041 | |
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| 0.505 | 2.4737 | 910 | 0.5039 | |
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| 0.4833 | 2.7237 | 1001 | 0.5038 | |
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| 0.4986 | 2.9736 | 1092 | 0.5037 | |
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| 0.5227 | 3.2108 | 1183 | 0.5037 | |
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| 0.5723 | 3.4607 | 1274 | 0.5037 | |
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| 0.4692 | 3.7106 | 1365 | 0.5037 | |
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| 0.5222 | 3.9605 | 1456 | 0.5037 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.42.3 |
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- Pytorch 2.1.2+cu118 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
