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--- |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-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_Sparse_refined_web_50p_2024-02-16 |
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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_Sparse_refined_web_50p_2024-02-16 |
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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: 2.1260 |
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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: 1e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 0 |
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- distributed_type: multi-GPU |
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- num_devices: 3 |
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- gradient_accumulation_steps: 3 |
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- total_train_batch_size: 9 |
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- total_eval_batch_size: 3 |
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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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- 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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| 2.5975 | 0.01 | 25 | 2.6362 | |
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| 2.3082 | 0.01 | 50 | 2.5659 | |
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| 2.4024 | 0.02 | 75 | 2.5151 | |
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| 2.3358 | 0.02 | 100 | 2.4817 | |
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| 2.2267 | 0.03 | 125 | 2.4660 | |
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| 2.271 | 0.04 | 150 | 2.4456 | |
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| 2.1709 | 0.04 | 175 | 2.4413 | |
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| 2.2549 | 0.05 | 200 | 2.4306 | |
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| 2.2536 | 0.05 | 225 | 2.4243 | |
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| 2.2234 | 0.06 | 250 | 2.4212 | |
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| 2.2516 | 0.07 | 275 | 2.4202 | |
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| 2.2827 | 0.07 | 300 | 2.4146 | |
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| 2.1774 | 0.08 | 325 | 2.4156 | |
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| 2.278 | 0.08 | 350 | 2.4094 | |
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| 2.204 | 0.09 | 375 | 2.4088 | |
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| 2.1987 | 0.1 | 400 | 2.4073 | |
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| 2.1985 | 0.1 | 425 | 2.4041 | |
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| 2.2198 | 0.11 | 450 | 2.4069 | |
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| 2.2555 | 0.11 | 475 | 2.4014 | |
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| 2.1567 | 0.12 | 500 | 2.4017 | |
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| 2.2918 | 0.13 | 525 | 2.3998 | |
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| 2.2559 | 0.13 | 550 | 2.3959 | |
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| 2.2234 | 0.14 | 575 | 2.3978 | |
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| 2.2001 | 0.14 | 600 | 2.3944 | |
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| 2.1409 | 0.15 | 625 | 2.3957 | |
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| 2.2034 | 0.16 | 650 | 2.3981 | |
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| 2.1863 | 0.16 | 675 | 2.3941 | |
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| 2.2372 | 0.17 | 700 | 2.3936 | |
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| 2.2438 | 0.17 | 725 | 2.3953 | |
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| 2.2172 | 0.18 | 750 | 2.3943 | |
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| 2.1917 | 0.19 | 775 | 2.3921 | |
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| 2.1137 | 0.19 | 800 | 2.3912 | |
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| 2.0766 | 0.07 | 825 | 2.3935 | |
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| 2.1926 | 0.08 | 850 | 2.3913 | |
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| 2.2948 | 0.08 | 875 | 2.3915 | |
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| 2.1349 | 0.08 | 900 | 2.3917 | |
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| 2.2446 | 0.08 | 925 | 2.3876 | |
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| 2.253 | 0.09 | 950 | 2.3880 | |
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| 2.0729 | 0.09 | 975 | 2.3890 | |
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| 2.1965 | 0.09 | 1000 | 2.3873 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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