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mistral-lp2-org_aug_b

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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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+ - 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: org_model
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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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+ # org_model
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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: 0.9527
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+ - F1 Micro: 0.8011
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+ - F1 Macro: 0.7779
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+ - F1 Weighted: 0.8108
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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: 0.0001
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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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: linear
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+ - training_steps: 400
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | F1 Weighted |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|
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+ | 1.5515 | 0.0064 | 25 | 1.3111 | 0.7801 | 0.7504 | 0.7890 |
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+ | 1.2983 | 0.0127 | 50 | 1.2188 | 0.7748 | 0.7572 | 0.7891 |
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+ | 1.2193 | 0.0191 | 75 | 1.1271 | 0.7855 | 0.7583 | 0.7937 |
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+ | 1.1269 | 0.0255 | 100 | 1.0890 | 0.7952 | 0.7639 | 0.8015 |
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+ | 1.0734 | 0.0318 | 125 | 1.0594 | 0.7949 | 0.7635 | 0.8008 |
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+ | 1.0384 | 0.0382 | 150 | 1.0389 | 0.7857 | 0.7614 | 0.7937 |
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+ | 1.0168 | 0.0446 | 175 | 1.0126 | 0.8045 | 0.7794 | 0.8133 |
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+ | 1.0043 | 0.0510 | 200 | 0.9998 | 0.8034 | 0.7786 | 0.8123 |
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+ | 1.0406 | 0.0573 | 225 | 0.9874 | 0.8074 | 0.7803 | 0.8153 |
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+ | 1.0488 | 0.0637 | 250 | 0.9838 | 0.7922 | 0.7664 | 0.8000 |
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+ | 0.9894 | 0.0701 | 275 | 0.9673 | 0.8034 | 0.7780 | 0.8122 |
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+ | 0.9969 | 0.0764 | 300 | 0.9629 | 0.7992 | 0.7720 | 0.8069 |
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+ | 1.0047 | 0.0828 | 325 | 0.9655 | 0.8000 | 0.7689 | 0.8058 |
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+ | 0.9812 | 0.0892 | 350 | 0.9623 | 0.8049 | 0.7839 | 0.8159 |
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+ | 0.9681 | 0.0955 | 375 | 0.9551 | 0.8016 | 0.7794 | 0.8118 |
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+ | 1.0594 | 0.1019 | 400 | 0.9527 | 0.8011 | 0.7779 | 0.8108 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.10.0
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+ - Transformers 4.40.2
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+ - Pytorch 2.3.0+cu118
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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