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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_2024-03-21 |
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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_2024-03-21 |
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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: 2.1512 |
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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: 4 |
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- total_train_batch_size: 12 |
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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: 501 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.4177 | 0.0 | 25 | 2.6401 | |
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| 2.5407 | 0.01 | 50 | 2.5820 | |
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| 2.3887 | 0.01 | 75 | 2.5299 | |
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| 2.2849 | 0.01 | 100 | 2.4991 | |
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| 2.2042 | 0.01 | 125 | 2.4802 | |
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| 2.2574 | 0.02 | 150 | 2.4609 | |
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| 2.2353 | 0.02 | 175 | 2.4473 | |
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| 2.3355 | 0.02 | 200 | 2.4449 | |
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| 2.3044 | 0.03 | 225 | 2.4381 | |
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| 2.2664 | 0.03 | 250 | 2.4348 | |
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| 2.1999 | 0.03 | 275 | 2.4263 | |
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| 2.2631 | 0.04 | 300 | 2.4247 | |
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| 2.2918 | 0.04 | 325 | 2.4184 | |
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| 2.1426 | 0.04 | 350 | 2.4185 | |
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| 2.149 | 0.04 | 375 | 2.4158 | |
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| 2.1937 | 0.05 | 400 | 2.4129 | |
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| 2.2372 | 0.05 | 425 | 2.4134 | |
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| 2.1997 | 0.05 | 450 | 2.4123 | |
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| 2.2937 | 0.06 | 475 | 2.4086 | |
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| 2.3067 | 0.06 | 500 | 2.4052 | |
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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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