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--- |
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library_name: peft |
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license: apache-2.0 |
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base_model: mistralai/Mistral-Small-3.1-24B-Instruct-2503 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- combined_dataset.jsonl |
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model-index: |
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- name: combined_model-finetune |
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results: [] |
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--- |
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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/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: `0.10.0.dev0` |
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```yaml |
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# =================================================================== |
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# CONFIG: For a single, combined "Conversion & Debug" Model |
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# Using the stable 'alpaca' format. |
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# =================================================================== |
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# --- Core Model Configuration (Kept as requested) --- |
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base_model: mistralai/Mistral-Small-3.1-24B-Instruct-2503 |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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# --- Performance, Quality, and Memory Optimization --- |
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flash_attention: true |
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load_in_4bit: true |
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load_in_8bit: false |
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adapter: lora |
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# --- Dataset Configuration (KEY CHANGE) --- |
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# Reverted to the stable 'alpaca' type. |
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# Axolotl will automatically look for 'instruction', 'input', 'output' fields. |
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datasets: |
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- path: combined_dataset.jsonl # This is your new, flattened dataset |
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type: alpaca |
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# --- Output Directory --- |
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output_dir: ./combined_model-finetune |
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# --- Training Hyperparameters --- |
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sequence_len: 2048 |
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micro_batch_size: 1 |
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gradient_accumulation_steps: 4 |
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num_epochs: 3 |
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learning_rate: 3e-5 |
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# --- LoRA Configuration --- |
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lora_r: 16 |
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lora_alpha: 32 |
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lora_dropout: 0.15 |
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lora_target_modules: |
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- q_proj |
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- v_proj |
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- k_proj |
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- o_proj |
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# --- Logging, Evaluation, and Saving (Kept as requested) --- |
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logging_steps: 2 |
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evaluation_strategy: "steps" |
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eval_steps: 2 |
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save_strategy: "steps" |
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save_steps: 9999 |
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val_set_size: 0.05 |
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special_tokens: |
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bos_token: "<s>" |
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eos_token: "</s>" |
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unk_token: "<unk>" |
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``` |
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</details><br> |
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# combined_model-finetune |
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This model is a fine-tuned version of [mistralai/Mistral-Small-3.1-24B-Instruct-2503](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503) on the combined_dataset.jsonl dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1924 |
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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: 4 |
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- total_train_batch_size: 4 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- training_steps: 21 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| No log | 0.1481 | 1 | 0.2836 | |
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| 0.2664 | 0.2963 | 2 | 0.2538 | |
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| 0.4832 | 0.5926 | 4 | 0.2200 | |
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| 0.3229 | 0.8889 | 6 | 0.2090 | |
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| 0.1517 | 1.1481 | 8 | 0.2022 | |
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| 0.3353 | 1.4444 | 10 | 0.2009 | |
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| 0.2418 | 1.7407 | 12 | 0.1958 | |
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| 0.0811 | 2.0 | 14 | 0.1942 | |
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| 0.0496 | 2.2963 | 16 | 0.1933 | |
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| 0.1906 | 2.5926 | 18 | 0.1927 | |
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| 0.3171 | 2.8889 | 20 | 0.1924 | |
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### Framework versions |
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- PEFT 0.15.2 |
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- Transformers 4.52.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
