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rishavranaut/Mistral_final_Task2_2.0

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  2. adapter_model.safetensors +1 -1
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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+ metrics:
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+ - accuracy
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+ - precision
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+ - recall
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+ model-index:
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+ - name: Mistral_final_Task2_2.0
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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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+ # Mistral_final_Task2_2.0
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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: 0.5570
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+ - Accuracy: 0.8943
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+ - Precision: 0.9184
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+ - Recall: 0.8661
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+ - F1 score: 0.8915
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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: 16
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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: linear
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 score |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
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+ | 0.9274 | 0.5450 | 200 | 0.6669 | 0.8371 | 0.9072 | 0.7521 | 0.8224 |
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+ | 0.5321 | 1.0899 | 400 | 1.0293 | 0.7986 | 0.9861 | 0.6068 | 0.7513 |
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+ | 0.4279 | 1.6349 | 600 | 1.0278 | 0.7586 | 0.6904 | 0.9402 | 0.7961 |
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+ | 0.3054 | 2.1798 | 800 | 0.4428 | 0.8714 | 0.8575 | 0.8917 | 0.8743 |
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+ | 0.2297 | 2.7248 | 1000 | 0.5243 | 0.8743 | 0.9428 | 0.7977 | 0.8642 |
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+ | 0.1798 | 3.2698 | 1200 | 0.4710 | 0.8971 | 0.9043 | 0.8889 | 0.8966 |
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+ | 0.158 | 3.8147 | 1400 | 0.5673 | 0.8986 | 0.9545 | 0.8376 | 0.8923 |
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+ | 0.0921 | 4.3597 | 1600 | 0.5847 | 0.8743 | 0.8380 | 0.9288 | 0.8811 |
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+ | 0.063 | 4.9046 | 1800 | 0.5570 | 0.8943 | 0.9184 | 0.8661 | 0.8915 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
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+ - Transformers 4.44.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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