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README.md ADDED
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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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+ - trl
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+ - sft
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+ - generated_from_trainer
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+ base_model: mistralai/Mistral-7B-v0.1
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+ model-index:
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+ - name: NXAIR_M_mistral-7B
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+ results: []
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+ ---
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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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+
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+ # NXAIR_M_mistral-7B
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+
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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: 0.8905
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.00025
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+ - train_batch_size: 4
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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: constant
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+ - lr_scheduler_warmup_ratio: 0.03
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+ - num_epochs: 15
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.0223 | 0.39 | 100 | 1.0286 |
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+ | 0.9037 | 0.78 | 200 | 0.8790 |
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+ | 0.5836 | 1.16 | 300 | 0.7868 |
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+ | 0.5867 | 1.55 | 400 | 0.7354 |
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+ | 0.5663 | 1.94 | 500 | 0.7268 |
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+ | 0.4228 | 2.33 | 600 | 0.7649 |
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+ | 0.423 | 2.71 | 700 | 0.7254 |
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+ | 0.3011 | 3.1 | 800 | 0.7822 |
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+ | 0.3317 | 3.49 | 900 | 0.7891 |
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+ | 0.3722 | 3.88 | 1000 | 0.8496 |
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+ | 0.3005 | 4.26 | 1100 | 0.7813 |
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+ | 0.3101 | 4.65 | 1200 | 0.7908 |
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+ | 0.3549 | 5.04 | 1300 | 0.7937 |
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+ | 0.3198 | 5.43 | 1400 | 0.7881 |
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+ | 0.2999 | 5.81 | 1500 | 0.7738 |
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+ | 0.2822 | 6.2 | 1600 | 0.8227 |
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+ | 0.2977 | 6.59 | 1700 | 0.8299 |
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+ | 0.3066 | 6.98 | 1800 | 0.8399 |
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+ | 0.2704 | 7.36 | 1900 | 0.8435 |
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+ | 0.2703 | 7.75 | 2000 | 0.8527 |
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+ | 0.2281 | 8.14 | 2100 | 0.8745 |
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+ | 0.2321 | 8.53 | 2200 | 0.8396 |
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+ | 0.2528 | 8.91 | 2300 | 0.8342 |
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+ | 0.2177 | 9.3 | 2400 | 0.8183 |
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+ | 0.245 | 9.69 | 2500 | 0.8264 |
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+ | 0.1965 | 10.08 | 2600 | 0.8772 |
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+ | 0.2107 | 10.47 | 2700 | 0.8543 |
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+ | 0.2178 | 10.85 | 2800 | 0.8353 |
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+ | 0.2091 | 11.24 | 2900 | 0.8685 |
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+ | 0.2253 | 11.63 | 3000 | 0.8220 |
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+ | 0.2395 | 12.02 | 3100 | 0.8233 |
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+ | 0.2216 | 12.4 | 3200 | 0.9099 |
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+ | 0.2392 | 12.79 | 3300 | 0.8779 |
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+ | 0.237 | 13.18 | 3400 | 0.9224 |
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+ | 0.227 | 13.57 | 3500 | 0.8935 |
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+ | 0.231 | 13.95 | 3600 | 0.9021 |
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+ | 0.1922 | 14.34 | 3700 | 0.9564 |
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+ | 0.211 | 14.73 | 3800 | 0.8905 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.8.2
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+ - Transformers 4.37.2
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+ - Pytorch 2.2.0+cu121
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+ - Datasets 2.17.0
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+ - Tokenizers 0.15.2
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