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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-Instruct-v0.3 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: mistral-7b-instruct-v0.3-mimic4-adapt-l2r |
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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-v0.3-mimic4-adapt-l2r |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: -438158728757996992.0000 |
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- Ndcg: 0.9571 |
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- Ndcg@25: 0.8843 |
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- Precision@25: 0.9634 |
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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: 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 adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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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 | Ndcg | Ndcg@25 | Precision@25 | |
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|:-------------------------:|:------:|:----:|:------------------------:|:------:|:-------:|:------------:| |
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| -1114019463802178816.0000 | 1.0 | 44 | -109312091402722160.0000 | 0.9555 | 0.2112 | 0.0 | |
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| -97186389406882208.0000 | 2.0 | 88 | -332415755916448320.0000 | 0.9562 | 0.7834 | 0.5920 | |
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| -1330305825467111936.0000 | 3.0 | 132 | -391117015460168128.0000 | 0.9569 | 0.8217 | 0.9086 | |
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| -355019110469337088.0000 | 4.0 | 176 | -415820224368131648.0000 | 0.9570 | 0.8829 | 0.9360 | |
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| -4554729996694637568.0000 | 4.9017 | 215 | -438158728757996992.0000 | 0.9571 | 0.8843 | 0.9634 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.6.0 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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