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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: facebook/esm2_t33_650M_UR50D
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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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+ - precision
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+ - recall
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+ model-index:
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+ - name: esm2_t33_650M_UR50D-finetuned
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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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+ # esm2_t33_650M_UR50D-finetuned
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+
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+ This model is a fine-tuned version of [facebook/esm2_t33_650M_UR50D](https://huggingface.co/facebook/esm2_t33_650M_UR50D) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4409
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+ - Tp: 539
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+ - Tn: 617
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+ - Fp: 47
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+ - Fn: 93
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+ - Accuracy: 0.8920
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+ - Precision: 0.9198
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+ - Recall: 0.8528
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+ - F1-score: 0.8851
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+ - Auc: 0.8910
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+ - Mcc: 0.7854
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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: 2e-05
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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: linear
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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 | Tp | Tn | Fp | Fn | Accuracy | Precision | Recall | F1-score | Auc | Mcc |
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+ |:-------------:|:-----:|:----:|:---------------:|:---:|:---:|:--:|:---:|:--------:|:---------:|:------:|:--------:|:------:|:------:|
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+ | 0.393 | 1.0 | 1296 | 0.3616 | 507 | 615 | 49 | 125 | 0.8657 | 0.9119 | 0.8022 | 0.8535 | 0.8642 | 0.7356 |
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+ | 0.3052 | 2.0 | 2592 | 0.3159 | 536 | 608 | 56 | 96 | 0.8827 | 0.9054 | 0.8481 | 0.8758 | 0.8819 | 0.7664 |
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+ | 0.166 | 3.0 | 3888 | 0.4409 | 539 | 617 | 47 | 93 | 0.8920 | 0.9198 | 0.8528 | 0.8851 | 0.8910 | 0.7854 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.2
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+ - Pytorch 1.13.1+cu117
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.1
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