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esm2_t12_35M_UR50D-finetuned-binding-classification
lovegemini63/esm2_t12_35M_UR50D-finetuned-binding-classification
esm2_t12_35M_UR50D-finetuned-binding-classification is a text classification model from lovegemini63. 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
- Sep 20, 2023
- Updated
- Sep 20, 2023
- SHA
- b2251be1
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Base models
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-binding-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: 0.4948
- Train Accuracy: 0.7534
- Validation Loss: 0.5392
- Validation Accuracy: 0.7253
- 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 |
|---|---|---|---|---|
| 0.5196 | 0.7364 | 0.5415 | 0.7249 | 0 |
| 0.5037 | 0.7469 | 0.5433 | 0.7277 | 1 |
| 0.4948 | 0.7534 | 0.5392 | 0.7253 | 2 |
Framework versions
- Transformers 4.33.2
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- esm
- License
- mit
- Created
- Sep 20, 2023
- Updated
- Sep 20, 2023