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esm2_t12_35M_UR50D-finetuned-cytosol-membrane-classification
miangoar/esm2_t12_35M_UR50D-finetuned-cytosol-membrane-classification
esm2_t12_35M_UR50D-finetuned-cytosol-membrane-classification is a text classification model from miangoar. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- esm
- Access
- Public
- Created
- Dec 15, 2022
- Updated
- Dec 15, 2022
- SHA
- 946b89c2
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
esm2_t12_35M_UR50D-finetuned-cytosol-membrane-classification
This model is a fine-tuned version of facebook/esm2_t12_35M_UR50D on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.1009
- Train Accuracy: 0.9684
- Validation Loss: 0.2122
- Validation Accuracy: 0.9401
- Epoch: 2
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.0}
- training_precision: float32
Training results
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|---|---|---|---|---|
| 0.2464 | 0.9228 | 0.1954 | 0.9417 | 0 |
| 0.1428 | 0.9565 | 0.1831 | 0.9345 | 1 |
| 0.1009 | 0.9684 | 0.2122 | 0.9401 | 2 |
Framework versions
- Transformers 4.25.1
- TensorFlow 2.9.2
- Datasets 2.7.1
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- esm
- License
- mit
- Created
- Dec 15, 2022
- Updated
- Dec 15, 2022