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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/Mixtral-8x7B-v0.1 |
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model-index: |
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- name: mixtral-8x7b-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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# mixtral-8x7b-v0.1-english-to-hinglish-translation |
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This model is a fine-tuned version of [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0769 |
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- Rouge Scores: {'rouge1': 0.9045408202972536, 'rouge2': 0.795425441228359, 'rougeL': 0.8399846297860634, 'rougeLsum': 0.9043739034131012} |
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- Bleu Scores: [0.0002881182166187815, 0.0002842750061873772, 0.0002764768847375588, 0.00026750640347869873] |
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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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| 1.1771 | 1.0 | 500 | 1.0579 | {'rouge1': 0.9070255400902434, 'rouge2': 0.7976770190068221, 'rougeL': 0.8400261479965636, 'rougeLsum': 0.9069363147075731} | [0.00028395954091190866, 0.0002796973368739713, 0.0002722057765709132, 0.000263740024418467] | 2047.996 | |
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| 0.7788 | 2.0 | 1000 | 1.0769 | {'rouge1': 0.90.45408202972536, 'rouge2': 0.795425441228359, 'rougeL': 0.8399846297860634, 'rougeLsum': 0.9043739034131012} | [0.0002881182166187815, 0.0002842750061873772, 0.0002764768847375588, 0.00026750640347869873] | 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 |
