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pfam_4class_seq

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README.md ADDED
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+ ---
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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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+ model-index:
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+ - name: esm2_t33_650M_UR50D-uniprot-7class-uniprot-7class
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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-uniprot-7class-uniprot-7class
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+
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+ This model was trained from scratch on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1818
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+ - Accuracy: 0.9593
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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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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 128
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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: 10
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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 |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | No log | 0.9846 | 4 | 0.3113 | 0.9244 |
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+ | No log | 1.9692 | 8 | 0.2729 | 0.9244 |
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+ | No log | 2.9538 | 12 | 0.2448 | 0.9360 |
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+ | No log | 3.9385 | 16 | 0.2138 | 0.9477 |
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+ | No log | 4.9231 | 20 | 0.1997 | 0.9651 |
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+ | No log | 5.9077 | 24 | 0.1934 | 0.9593 |
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+ | No log | 6.8923 | 28 | 0.1901 | 0.9593 |
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+ | No log | 7.8769 | 32 | 0.1847 | 0.9593 |
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+ | No log | 8.8615 | 36 | 0.1824 | 0.9593 |
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+ | No log | 9.8462 | 40 | 0.1818 | 0.9593 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.2
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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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+ "EsmForSequenceClassification"
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