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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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base_model: mistralai/Mistral-7B-Instruct-v0.2 |
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datasets: |
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- generator |
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metrics: |
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- bleu |
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- rouge |
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model-index: |
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- name: Mistral-7B-Instruct-v0.2-advisegpt-v0.6 |
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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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# Mistral-7B-Instruct-v0.2-advisegpt-v0.6 |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0767 |
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- Bleu: {'bleu': 0.9584832765902116, 'precisions': [0.9778312591422885, 0.9625878953932084, 0.9518774970032065, 0.9430684559898991], 'brevity_penalty': 0.9997177244264667, 'length_ratio': 0.9997177642587203, 'translation_length': 1289338, 'reference_length': 1289702} |
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- Rouge: {'rouge1': 0.9761023152523122, 'rouge2': 0.9590922549283836, 'rougeL': 0.9747297976860183, 'rougeLsum': 0.9758442544146716} |
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- Exact Match: {'exact_match': 0.0} |
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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: 2e-05 |
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- train_batch_size: 3 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 10 |
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- total_train_batch_size: 30 |
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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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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge | Exact Match | |
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|:-------------:|:------:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------------------------:|:--------------------:| |
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| 0.067 | 0.9998 | 809 | 0.0945 | {'bleu': 0.9492918853166353, 'precisions': [0.9733554685833311, 0.9543042005762523, 0.9412361771045687, 0.9307382413966919], 'brevity_penalty': 0.9994904502180469, 'length_ratio': 0.9994905799944483, 'translation_length': 1289045, 'reference_length': 1289702} | {'rouge1': 0.9712558044405124, 'rouge2': 0.9500703853191179, 'rougeL': 0.9690578078497468, 'rougeLsum': 0.9708044674114953} | {'exact_match': 0.0} | |
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| 0.0527 | 1.9995 | 1618 | 0.0779 | {'bleu': 0.9568445996007577, 'precisions': [0.977026202258449, 0.961055539100332, 0.9498195483213825, 0.9405540074014527], 'brevity_penalty': 0.9998193217903225, 'length_ratio': 0.9998193381106644, 'translation_length': 1289469, 'reference_length': 1289702} | {'rouge1': 0.9753094821779227, 'rouge2': 0.9574822736836266, 'rougeL': 0.9737984768450723, 'rougeLsum': 0.9750220632065946} | {'exact_match': 0.0} | |
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| 0.0471 | 2.9993 | 2427 | 0.0767 | {'bleu': 0.9584832765902116, 'precisions': [0.9778312591422885, 0.9625878953932084, 0.9518774970032065, 0.9430684559898991], 'brevity_penalty': 0.9997177244264667, 'length_ratio': 0.9997177642587203, 'translation_length': 1289338, 'reference_length': 1289702} | {'rouge1': 0.9761023152523122, 'rouge2': 0.9590922549283836, 'rougeL': 0.9747297976860183, 'rougeLsum': 0.9758442544146716} | {'exact_match': 0.0} | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
