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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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- generated_from_trainer |
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base_model: filipealmeida/Mistral-7B-Instruct-v0.1-sharded |
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model-index: |
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- name: mistral7b-finetune-20k-withnoclass |
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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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# mistral7b-finetune-20k-withnoclass |
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This model is a fine-tuned version of [filipealmeida/Mistral-7B-Instruct-v0.1-sharded](https://huggingface.co/filipealmeida/Mistral-7B-Instruct-v0.1-sharded) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9941 |
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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: 0.0002 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- training_steps: 2500 |
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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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| 1.8094 | 0.04 | 100 | 1.4332 | |
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| 1.274 | 0.08 | 200 | 1.2291 | |
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| 1.1812 | 0.12 | 300 | 1.1865 | |
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| 1.1474 | 0.16 | 400 | 1.1542 | |
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| 1.1421 | 0.2 | 500 | 1.1370 | |
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| 1.101 | 0.24 | 600 | 1.1154 | |
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| 1.1111 | 0.29 | 700 | 1.0999 | |
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| 1.0778 | 0.33 | 800 | 1.0841 | |
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| 1.0421 | 0.37 | 900 | 1.0784 | |
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| 1.0468 | 0.41 | 1000 | 1.0644 | |
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| 1.0389 | 0.45 | 1100 | 1.0540 | |
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| 1.0023 | 0.49 | 1200 | 1.0434 | |
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| 1.0396 | 0.53 | 1300 | 1.0342 | |
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| 0.9991 | 0.57 | 1400 | 1.0260 | |
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| 1.0304 | 0.61 | 1500 | 1.0238 | |
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| 1.0033 | 0.65 | 1600 | 1.0159 | |
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| 1.0065 | 0.69 | 1700 | 1.0109 | |
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| 0.9587 | 0.73 | 1800 | 1.0072 | |
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| 0.9725 | 0.78 | 1900 | 1.0025 | |
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| 0.9738 | 0.82 | 2000 | 0.9997 | |
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| 0.9816 | 0.86 | 2100 | 0.9972 | |
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| 0.9858 | 0.9 | 2200 | 0.9956 | |
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| 0.9477 | 0.94 | 2300 | 0.9946 | |
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| 0.9834 | 0.98 | 2400 | 0.9941 | |
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| 0.943 | 1.02 | 2500 | 0.9941 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.0 |
