---

license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B
tags:
- generated_from_trainer
model-index:
- name: workspace/axolotl/dolphin-2.9.4-llama3.1-8b
  results: []

---

![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)

# QuantFactory/dolphin-2.9.4-llama3.1-8b-GGUF
This is quantized version of [cognitivecomputations/dolphin-2.9.4-llama3.1-8b](https://huggingface.co./cognitivecomputations/dolphin-2.9.4-llama3.1-8b) created using llama.cpp

# Original Model Card


# warning - it's not working yet, recommend hold off on downloading

<details><summary>Evals</summary>

```
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)
|                           Tasks                           |Version|Filter|n-shot|        Metric         |   |Value |   |Stderr|
|-----------------------------------------------------------|-------|------|-----:|-----------------------|---|-----:|---|------|
|leaderboard                                                |N/A    |none  |     0|acc                    |↑  |0.2926|±  |0.0041|
|                                                           |       |none  |     0|acc_norm               |↑  |0.4513|±  |0.0053|
|                                                           |       |none  |     0|exact_match            |↑  |0.0982|±  |0.0079|
|                                                           |       |none  |     0|inst_level_loose_acc   |↑  |0.3825|±  |N/A   |
|                                                           |       |none  |     0|inst_level_strict_acc  |↑  |0.3597|±  |N/A   |
|                                                           |       |none  |     0|prompt_level_loose_acc |↑  |0.2421|±  |0.0184|
|                                                           |       |none  |     0|prompt_level_strict_acc|↑  |0.2181|±  |0.0178|
| - leaderboard_bbh                                         |N/A    |none  |     3|acc_norm               |↑  |0.4931|±  |0.0061|
|  - leaderboard_bbh_boolean_expressions                    |      0|none  |     3|acc_norm               |↑  |0.8000|±  |0.0253|
|  - leaderboard_bbh_causal_judgement                       |      0|none  |     3|acc_norm               |↑  |0.5615|±  |0.0364|
|  - leaderboard_bbh_date_understanding                     |      0|none  |     3|acc_norm               |↑  |0.4520|±  |0.0315|
|  - leaderboard_bbh_disambiguation_qa                      |      0|none  |     3|acc_norm               |↑  |0.6640|±  |0.0299|
|  - leaderboard_bbh_formal_fallacies                       |      0|none  |     3|acc_norm               |↑  |0.5600|±  |0.0315|
|  - leaderboard_bbh_geometric_shapes                       |      0|none  |     3|acc_norm               |↑  |0.3640|±  |0.0305|
|  - leaderboard_bbh_hyperbaton                             |      0|none  |     3|acc_norm               |↑  |0.6320|±  |0.0306|
|  - leaderboard_bbh_logical_deduction_five_objects         |      0|none  |     3|acc_norm               |↑  |0.4600|±  |0.0316|
|  - leaderboard_bbh_logical_deduction_seven_objects        |      0|none  |     3|acc_norm               |↑  |0.4360|±  |0.0314|
|  - leaderboard_bbh_logical_deduction_three_objects        |      0|none  |     3|acc_norm               |↑  |0.6160|±  |0.0308|
|  - leaderboard_bbh_movie_recommendation                   |      0|none  |     3|acc_norm               |↑  |0.7880|±  |0.0259|
|  - leaderboard_bbh_navigate                               |      0|none  |     3|acc_norm               |↑  |0.5200|±  |0.0317|
|  - leaderboard_bbh_object_counting                        |      0|none  |     3|acc_norm               |↑  |0.4520|±  |0.0315|
|  - leaderboard_bbh_penguins_in_a_table                    |      0|none  |     3|acc_norm               |↑  |0.5205|±  |0.0415|
|  - leaderboard_bbh_reasoning_about_colored_objects        |      0|none  |     3|acc_norm               |↑  |0.5120|±  |0.0317|
|  - leaderboard_bbh_ruin_names                             |      0|none  |     3|acc_norm               |↑  |0.6320|±  |0.0306|
|  - leaderboard_bbh_salient_translation_error_detection    |      0|none  |     3|acc_norm               |↑  |0.4320|±  |0.0314|
|  - leaderboard_bbh_snarks                                 |      0|none  |     3|acc_norm               |↑  |0.5843|±  |0.0370|
|  - leaderboard_bbh_sports_understanding                   |      0|none  |     3|acc_norm               |↑  |0.7040|±  |0.0289|
|  - leaderboard_bbh_temporal_sequences                     |      0|none  |     3|acc_norm               |↑  |0.1440|±  |0.0222|
|  - leaderboard_bbh_tracking_shuffled_objects_five_objects |      0|none  |     3|acc_norm               |↑  |0.1560|±  |0.0230|
|  - leaderboard_bbh_tracking_shuffled_objects_seven_objects|      0|none  |     3|acc_norm               |↑  |0.1320|±  |0.0215|
|  - leaderboard_bbh_tracking_shuffled_objects_three_objects|      0|none  |     3|acc_norm               |↑  |0.2840|±  |0.0286|
|  - leaderboard_bbh_web_of_lies                            |      0|none  |     3|acc_norm               |↑  |0.4840|±  |0.0317|
| - leaderboard_gpqa                                        |N/A    |none  |     0|acc_norm               |↑  |0.2903|±  |0.0132|
|  - leaderboard_gpqa_diamond                               |      1|none  |     0|acc_norm               |↑  |0.2980|±  |0.0326|
|  - leaderboard_gpqa_extended                              |      1|none  |     0|acc_norm               |↑  |0.2839|±  |0.0193|
|  - leaderboard_gpqa_main                                  |      1|none  |     0|acc_norm               |↑  |0.2946|±  |0.0216|
| - leaderboard_ifeval                                      |      2|none  |     0|inst_level_loose_acc   |↑  |0.3825|±  |N/A   |
|                                                           |       |none  |     0|inst_level_strict_acc  |↑  |0.3597|±  |N/A   |
|                                                           |       |none  |     0|prompt_level_loose_acc |↑  |0.2421|±  |0.0184|
|                                                           |       |none  |     0|prompt_level_strict_acc|↑  |0.2181|±  |0.0178|
|  - leaderboard_math_algebra_hard                          |      1|none  |     4|exact_match            |↑  |0.1596|±  |0.0209|
|  - leaderboard_math_counting_and_prob_hard                |      1|none  |     4|exact_match            |↑  |0.0488|±  |0.0195|
|  - leaderboard_math_geometry_hard                         |      1|none  |     4|exact_match            |↑  |0.0530|±  |0.0196|
| - leaderboard_math_hard                                   |N/A    |none  |     4|exact_match            |↑  |0.0982|±  |0.0079|
|  - leaderboard_math_intermediate_algebra_hard             |      1|none  |     4|exact_match            |↑  |0.0143|±  |0.0071|
|  - leaderboard_math_num_theory_hard                       |      1|none  |     4|exact_match            |↑  |0.0455|±  |0.0168|
|  - leaderboard_math_prealgebra_hard                       |      1|none  |     4|exact_match            |↑  |0.2591|±  |0.0316|
|  - leaderboard_math_precalculus_hard                      |      1|none  |     4|exact_match            |↑  |0.0519|±  |0.0192|
| - leaderboard_mmlu_pro                                    |    0.1|none  |     5|acc                    |↑  |0.2926|±  |0.0041|
| - leaderboard_musr                                        |N/A    |none  |     0|acc_norm               |↑  |0.3862|±  |0.0173|
|  - leaderboard_musr_murder_mysteries                      |      1|none  |     0|acc_norm               |↑  |0.5280|±  |0.0316|
|  - leaderboard_musr_object_placements                     |      1|none  |     0|acc_norm               |↑  |0.3594|±  |0.0300|
|  - leaderboard_musr_team_allocation                       |      1|none  |     0|acc_norm               |↑  |0.2720|±  |0.0282|

|         Groups         |Version|Filter|n-shot|        Metric         |   |Value |   |Stderr|
|------------------------|-------|------|-----:|-----------------------|---|-----:|---|------|
|leaderboard             |N/A    |none  |     0|acc                    |↑  |0.2926|±  |0.0041|
|                        |       |none  |     0|acc_norm               |↑  |0.4513|±  |0.0053|
|                        |       |none  |     0|exact_match            |↑  |0.0982|±  |0.0079|
|                        |       |none  |     0|inst_level_loose_acc   |↑  |0.3825|±  |N/A   |
|                        |       |none  |     0|inst_level_strict_acc  |↑  |0.3597|±  |N/A   |
|                        |       |none  |     0|prompt_level_loose_acc |↑  |0.2421|±  |0.0184|
|                        |       |none  |     0|prompt_level_strict_acc|↑  |0.2181|±  |0.0178|
| - leaderboard_bbh      |N/A    |none  |     3|acc_norm               |↑  |0.4931|±  |0.0061|
| - leaderboard_gpqa     |N/A    |none  |     0|acc_norm               |↑  |0.2903|±  |0.0132|
| - leaderboard_math_hard|N/A    |none  |     4|exact_match            |↑  |0.0982|±  |0.0079|
| - leaderboard_musr     |N/A    |none  |     0|acc_norm               |↑  |0.3862|±  |0.0173|
```

</details>

[<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)
<details><summary>See axolotl config</summary>

axolotl version: `0.4.1`
```yaml
base_model: meta-llama/Meta-Llama-3.1-8B
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
# load_in_4bit: true
strict: false

datasets:
  - path: /workspace/datasets/dolphin-2.9.4/dolphin201-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml

chat_template: chatml
# adapter: qlora
# lora_r: 128
# lora_alpha: 16
# lora_modules_to_save: [embed_tokens, lm_head]
# lora_dropout: 0.05
# lora_target_linear: true

unfrozen_parameters:
- input_layernorm
- model.norm
- post_attention_layernorm
- self_attn.rotary_emb
- ^lm_head.weight$
- ^model.embed_tokens.weight$
# mlp.down_proj layers
- model.layers.1.mlp.down_proj
- model.layers.0.mlp.down_proj
- model.layers.30.mlp.down_proj
- model.layers.2.mlp.down_proj
- model.layers.21.mlp.down_proj
- model.layers.22.mlp.down_proj
- model.layers.29.mlp.down_proj
- model.layers.5.mlp.down_proj
- model.layers.4.mlp.down_proj
- model.layers.20.mlp.down_proj
- model.layers.23.mlp.down_proj
- model.layers.19.mlp.down_proj
- model.layers.3.mlp.down_proj
- model.layers.17.mlp.down_proj
- model.layers.6.mlp.down_proj
- model.layers.31.mlp.down_proj
# mlp.up_proj layers
- model.layers.4.mlp.up_proj
- model.layers.3.mlp.up_proj
- model.layers.0.mlp.up_proj
- model.layers.5.mlp.up_proj
- model.layers.7.mlp.up_proj
- model.layers.6.mlp.up_proj
- model.layers.2.mlp.up_proj
- model.layers.1.mlp.up_proj
- model.layers.8.mlp.up_proj
- model.layers.12.mlp.up_proj
- model.layers.14.mlp.up_proj
- model.layers.9.mlp.up_proj
- model.layers.15.mlp.up_proj
- model.layers.17.mlp.up_proj
- model.layers.13.mlp.up_proj
- model.layers.19.mlp.up_proj
# self_attn.k_proj layers
- model.layers.29.self_attn.k_proj
- model.layers.25.self_attn.k_proj
- model.layers.23.self_attn.k_proj
- model.layers.28.self_attn.k_proj
- model.layers.21.self_attn.k_proj
- model.layers.19.self_attn.k_proj
- model.layers.22.self_attn.k_proj
- model.layers.20.self_attn.k_proj
- model.layers.24.self_attn.k_proj
- model.layers.31.self_attn.k_proj
- model.layers.27.self_attn.k_proj
- model.layers.26.self_attn.k_proj
- model.layers.17.self_attn.k_proj
- model.layers.11.self_attn.k_proj
- model.layers.18.self_attn.k_proj
- model.layers.14.self_attn.k_proj
# self_attn.o_proj layers
- model.layers.14.self_attn.o_proj
- model.layers.7.self_attn.o_proj
- model.layers.5.self_attn.o_proj
- model.layers.11.self_attn.o_proj
- model.layers.6.self_attn.o_proj
- model.layers.24.self_attn.o_proj
- model.layers.9.self_attn.o_proj
- model.layers.13.self_attn.o_proj
- model.layers.10.self_attn.o_proj
- model.layers.12.self_attn.o_proj
- model.layers.8.self_attn.o_proj
- model.layers.25.self_attn.o_proj
- model.layers.21.self_attn.o_proj
- model.layers.23.self_attn.o_proj
- model.layers.15.self_attn.o_proj
- model.layers.16.self_attn.o_proj
# self_attn.q_proj layers
- model.layers.8.self_attn.q_proj
- model.layers.13.self_attn.q_proj
- model.layers.9.self_attn.q_proj
- model.layers.14.self_attn.q_proj
- model.layers.10.self_attn.q_proj
- model.layers.11.self_attn.q_proj
- model.layers.0.self_attn.q_proj
- model.layers.15.self_attn.q_proj
- model.layers.1.self_attn.q_proj
- model.layers.6.self_attn.q_proj
- model.layers.5.self_attn.q_proj
- model.layers.7.self_attn.q_proj
- model.layers.12.self_attn.q_proj
- model.layers.16.self_attn.q_proj
- model.layers.17.self_attn.q_proj
- model.layers.26.self_attn.q_proj
# self_attn.v_proj layers
- model.layers.26.self_attn.v_proj
- model.layers.17.self_attn.v_proj
- model.layers.3.self_attn.v_proj
- model.layers.28.self_attn.v_proj
- model.layers.29.self_attn.v_proj
- model.layers.21.self_attn.v_proj
- model.layers.15.self_attn.v_proj
- model.layers.16.self_attn.v_proj
- model.layers.20.self_attn.v_proj
- model.layers.25.self_attn.v_proj
- model.layers.6.self_attn.v_proj
- model.layers.23.self_attn.v_proj
- model.layers.4.self_attn.v_proj
- model.layers.1.self_attn.v_proj
- model.layers.22.self_attn.v_proj
- model.layers.14.self_attn.v_proj
# mlp.gate_proj layers
- model.layers.1.mlp.gate_proj
- model.layers.2.mlp.gate_proj
- model.layers.3.mlp.gate_proj
- model.layers.4.mlp.gate_proj
- model.layers.0.mlp.gate_proj
- model.layers.25.mlp.gate_proj
- model.layers.26.mlp.gate_proj
- model.layers.5.mlp.gate_proj
- model.layers.24.mlp.gate_proj
- model.layers.28.mlp.gate_proj
- model.layers.23.mlp.gate_proj
- model.layers.27.mlp.gate_proj
- model.layers.21.mlp.gate_proj
- model.layers.22.mlp.gate_proj
- model.layers.29.mlp.gate_proj
- model.layers.20.mlp.gate_proj




dataset_prepared_path:  /workspace/axolotl/dolph-2.9.4-nemo-prepared
val_set_size: 0.01
output_dir: /workspace/axolotl/dolphin-2.9.4-llama3.1-8b

sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true

wandb_project: dolphin-2.9.4-llama3.1-8b
wandb_watch:
wandb_run_id:
wandb_log_model:

gradient_accumulation_steps: 16
micro_batch_size: 2
num_epochs: 3
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 5e-6
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32:

gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 100
# evals_per_epoch: 4
eval_table_size:
saves_per_epoch: 1
save_total_limit: 2
save_steps:
debug:
deepspeed: deepspeed_configs/zero3_bf16.json
weight_decay: 0.1
special_tokens:
  eos_token: "<|im_end|>"
  bos_token: "<|begin_of_text|>"
  pad_token: "<|finetune_right_pad_id|>"
tokens:
  - "<|im_start|>"


# fsdp:
#   - full_shard
#   - auto_wrap
# fsdp_config:
#   fsdp_limit_all_gathers: true
#   fsdp_sync_module_states: true
#   fsdp_offload_params: true
#   fsdp_use_orig_params: false
#   fsdp_cpu_ram_efficient_loading: true
#   fsdp_transformer_layer_cls_to_wrap: MixtralSparseMoeBlock
#   fsdp_state_dict_type: FULL_STATE_DICT
#   fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
#   fsdp_sharding_strategy: FULL_SHARD
#   fsdp_forward_prefetch: false
#   fsdp_backward_prefetch: BACKWARD_PRE
```

</details><br>

# workspace/axolotl/dolphin-2.9.4-llama3.1-8b

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.
It achieves the following results on the evaluation set:
- Loss: 0.5655

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 16
- total_train_batch_size: 256
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.5837        | 1.0180 | 1161 | 0.5814          |
| 0.5525        | 2.0179 | 2322 | 0.5671          |
| 0.5514        | 2.9624 | 3420 | 0.5655          |


### Framework versions

- Transformers 4.44.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1