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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: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ |
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model-index: |
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- name: mistral-ft |
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results: [] |
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pipeline_tag: text2text-generation |
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widget: |
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- text: >- |
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Résultats :• Absence d’anomalie de densité parenchymateuse cérébrale, |
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cérébelleuse ou du tronc cérébral• Absence de dilatation du système |
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ventriculaire.• Structures médianes en place.• Absence de collection péri |
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cérébrale.• Absence de lésion osseuse.• Bonne pneumatisation des sinus. |
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example_title: Observation |
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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-ft |
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This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co./TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2527 |
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## Model description |
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This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co./TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) for radiology reports conclusions generation. |
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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: 0.0002 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 2 |
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- num_epochs: 10 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.3229 | 0.97 | 27 | 1.8742 | |
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| 1.7299 | 1.98 | 55 | 1.6318 | |
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| 1.5704 | 2.99 | 83 | 1.4831 | |
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| 1.4553 | 4.0 | 111 | 1.4052 | |
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| 1.4421 | 4.97 | 138 | 1.3805 | |
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| 1.3759 | 5.98 | 166 | 1.3759 | |
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| 1.3658 | 6.99 | 194 | 1.3355 | |
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| 1.3271 | 8.0 | 222 | 1.2890 | |
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| 1.3299 | 8.97 | 249 | 1.2618 | |
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| 1.2296 | 9.73 | 270 | 1.2527 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
