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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- text-generation-inference |
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- transformers |
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- unsloth |
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- mistral |
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- trl |
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base_model: unsloth/mistral-7b-instruct-v0.2-bnb-4bit |
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--- |
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# Uploaded model |
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- **Developed by:** Angelectronic |
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- **License:** apache-2.0 |
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- **Finetuned from model :** unsloth/mistral-7b-instruct-v0.2-bnb-4bit |
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This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. |
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) |
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### Evaluation |
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- **ViMMRC test set:** 0.7913 accuracy |
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### Training results |
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| Training Loss | Accuracy | Step | Validation Loss | |
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|:-------------:|:---------:|:-----:|:---------------:| |
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| 1.031300 | 0.764065 | 240 | 1.471467 | |
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| 0.854200 | 0.767695 | 480 | 1.459051 | |
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| 0.753000 | 0.791288 | 720 | 1.521693 | |
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| 0.669600 | 0.767695 | 960 | 1.521454 | |
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| 0.592300 | 0.771324 | 1200 | 1.590301 | |
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| 0.496500 | 0.780399 | 1440 | 1.608687 | |
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| 0.381800 | 0.785843 | 1680 | 1.641979 | |
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| 0.334100 | 0.769510 | 1920 | 1.629696 | |
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| 0.285500 | 0.769510 | 2160 | 1.715881 | |
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| 0.242200 | 0.765880 | 2400 | 1.747410 | |
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| 0.200000 | 0.773140 | 2640 | 1.813693 | |
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| 0.146800 | 0.765880 | 2880 | 1.937426 | |
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| 0.112200 | 0.776769 | 3120 | 1.937926 | |
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| 0.101500 | 0.765880 | 3360 | 1.997301 | |
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| 0.094200 | 0.764065 | 3600 | 1.968903 | |
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| 0.087000 | 0.758621 | 3840 | 2.004644 | |
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| 0.084600 | 0.762250 | 4080 | 2.010856 | |
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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: 16 |
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- eval_batch_size: 8 |
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- seed: 3407 |
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- gradient_accumulation_steps: 4 |
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- eval_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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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- lr_scheduler_warmup_steps: 5 |
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- num_epochs: 3 |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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