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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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- generated_from_trainer |
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base_model: mistralai/Mistral-7B-v0.1 |
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model-index: |
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- name: mistral-7b-v0.1-english-to-hinglish-translation |
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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-v0.1-english-to-hinglish-translation |
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9017 |
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- Rouge Scores: {'rouge1': 0.9052154858930703, 'rouge2': 0.7938118811886605, 'rougeL': 0.8365543601879399, 'rougeLsum': 0.9051011676969527} |
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- Bleu Scores: [0.9286814242037147, 0.9121661008968365, 0.8907823041130339, 0.8677722819236368] |
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- Gen Len: 2048.0 |
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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: 0.0001 |
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- train_batch_size: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 4 |
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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: 2 |
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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 | Rouge Scores | Bleu Scores | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-----------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------:|:-------:| |
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| 0.9667 | 1.0 | 500 | 0.8997 | {'rouge1': 0.9066197962103982, 'rouge2': 0.7949438120742293, 'rougeL': 0.8365583570941119, 'rougeLsum': 0.906542182776239} | [0.9280923249970773, 0.9116476390859075, 0.8901882800412136, 0.8671907395641425] | 2048.0 | |
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| 0.5702 | 2.0 | 1000 | 0.9017 | {'rouge1': 0.9052154858930703, 'rouge2': 0.7938118811886605, 'rougeL': 0.8365543601879399, 'rougeLsum': 0.9051011676969527} | [0.9286814242037147, 0.9121661008968365, 0.8907823041130339, 0.8677722819236368] | 2048.0 | |
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### Framework versions |
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- PEFT 0.8.2 |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.16.2.dev0 |
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- Tokenizers 0.15.1 |
