esm2_t12_35M_UR50D-finetuned-AMP_Classification_AntiGramPositive_doublePositiveCase – AI Model by qunfengd | AlphaNeural AI

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qunfengd/
esm2_t12_35M_UR50D-finetuned-AMP_Classification_AntiGramPositive_doublePositiveCase

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text-classification

generated_from_keras_callback

facebook/esm2_t12_35M_UR50D

autotrain_compatible

endpoints_compatible

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esm2_t12_35M_UR50D-finetuned-AMP_Classification_AntiGramPositive_doublePositiveCase

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: 0.0617
Train Accuracy: 0.9772
Validation Loss: 0.5210
Validation Accuracy: 0.8551
Epoch: 9

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
0.4862	0.7800	0.4257	0.8218	0
0.3768	0.8474	0.3845	0.8478	1
0.2799	0.8950	0.3625	0.8643	2
0.2042	0.9241	0.3613	0.8617	3
0.1502	0.9427	0.3833	0.8745	4
0.1228	0.9545	0.3959	0.8719	5
0.0935	0.9650	0.4453	0.8682	6
0.0786	0.9692	0.4728	0.8711	7
0.0682	0.9750	0.4915	0.8727	8
0.0617	0.9772	0.5210	0.8551	9

Framework versions

Transformers 4.40.2
TensorFlow 2.15.0
Datasets 2.19.1
Tokenizers 0.19.1