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--- |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-Instruct-v0.1 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: mistral-viggo-finetune |
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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-viggo-finetune |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4072 |
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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: 2.5e-05 |
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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: 4 |
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- total_train_batch_size: 8 |
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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: 5 |
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- training_steps: 1000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.4563 | 0.01 | 50 | 0.7277 | |
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| 0.5873 | 0.01 | 100 | 0.5276 | |
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| 0.4951 | 0.02 | 150 | 0.4817 | |
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| 0.4645 | 0.02 | 200 | 0.4664 | |
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| 0.4682 | 0.03 | 250 | 0.4541 | |
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| 0.4569 | 0.03 | 300 | 0.4447 | |
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| 0.4428 | 0.04 | 350 | 0.4362 | |
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| 0.4184 | 0.04 | 400 | 0.4326 | |
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| 0.4174 | 0.05 | 450 | 0.4280 | |
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| 0.4122 | 0.05 | 500 | 0.4242 | |
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| 0.4176 | 0.06 | 550 | 0.4228 | |
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| 0.4105 | 0.06 | 600 | 0.4175 | |
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| 0.4103 | 0.07 | 650 | 0.4154 | |
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| 0.4113 | 0.07 | 700 | 0.4133 | |
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| 0.3979 | 0.08 | 750 | 0.4118 | |
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| 0.3895 | 0.08 | 800 | 0.4109 | |
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| 0.4088 | 0.09 | 850 | 0.4092 | |
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| 0.399 | 0.09 | 900 | 0.4082 | |
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| 0.4001 | 0.1 | 950 | 0.4075 | |
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| 0.4067 | 0.1 | 1000 | 0.4072 | |
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### Framework versions |
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- Transformers 4.35.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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