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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_relu_2024-03-10 |
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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_relu_2024-03-10 |
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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: 2.5409 |
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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: 4 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- total_eval_batch_size: 4 |
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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: 600 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 8.7862 | 0.0 | 25 | 8.7098 | |
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| 8.1838 | 0.01 | 50 | 8.1781 | |
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| 7.7537 | 0.01 | 75 | 7.8068 | |
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| 7.5371 | 0.02 | 100 | 7.6076 | |
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| 7.2146 | 0.02 | 125 | 7.1801 | |
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| 4.832 | 0.02 | 150 | 4.7717 | |
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| 3.7768 | 0.03 | 175 | 3.8167 | |
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| 3.2705 | 0.03 | 200 | 3.4268 | |
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| 3.0907 | 0.04 | 225 | 3.2364 | |
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| 2.9979 | 0.04 | 250 | 3.1210 | |
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| 2.8613 | 0.04 | 275 | 3.0444 | |
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| 2.8331 | 0.05 | 300 | 2.9912 | |
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| 2.7972 | 0.05 | 325 | 2.9533 | |
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| 2.6097 | 0.06 | 350 | 2.9186 | |
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| 2.7506 | 0.06 | 375 | 2.8954 | |
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| 2.7809 | 0.06 | 400 | 2.8744 | |
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| 2.7346 | 0.07 | 425 | 2.8555 | |
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| 2.6997 | 0.07 | 450 | 2.8420 | |
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| 2.5839 | 0.08 | 475 | 2.8263 | |
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| 2.6435 | 0.08 | 500 | 2.8170 | |
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| 2.7207 | 0.08 | 525 | 2.8085 | |
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| 2.6248 | 0.09 | 550 | 2.7985 | |
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| 2.7277 | 0.09 | 575 | 2.7876 | |
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| 2.5448 | 0.1 | 600 | 2.7807 | |
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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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