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greatakela/mistral_multiclass_adapters

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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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+ metrics:
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+ - accuracy
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+ base_model: mistralai/Mistral-7B-v0.1
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+ model-index:
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+ - name: multilabel_classification
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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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+ # multilabel_classification
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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: 0.1275
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+ - F1 Micro: 0.8546
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+ - F1 Macro: 0.5865
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+ - Accuracy: 0.9780
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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: 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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 3
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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 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
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+ | No log | 1.0 | 255 | 0.2939 | 0.8282 | 0.5696 | 0.9604 |
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+ | 0.7587 | 2.0 | 510 | 0.1965 | 0.8546 | 0.5865 | 0.9780 |
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+ | 0.7587 | 3.0 | 765 | 0.1275 | 0.8546 | 0.5865 | 0.9780 |
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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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+ "target_modules": [
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+ "v_proj",
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+ ],
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+ "task_type": "SEQ_CLS",
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+ "use_rslora": false
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+ }
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