prot_bert-fine-tuned-toxicity_2.0.1 – AI Model by Niki548 | AlphaNeural AI

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Niki548/
prot_bert-fine-tuned-toxicity_2.0.1

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text-classification

generated_from_trainer

Rostlab/prot_bert

autotrain_compatible

endpoints_compatible

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prot_bert-fine-tuned-toxicity_2.0.1

This model is a fine-tuned version of Rostlab/prot_bert on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4239
Accuracy: 0.8387
Precision: 0.8391
Recall: 0.8387
F1: 0.8380

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:

learning_rate: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.6945	1.0	16	0.6730	0.7742	0.8401	0.7742	0.7558
0.6185	2.0	32	0.6087	0.8065	0.8093	0.8065	0.8044
0.5241	3.0	48	0.5501	0.8387	0.8391	0.8387	0.8380
0.466	4.0	64	0.5328	0.8387	0.8391	0.8387	0.8380
0.4281	5.0	80	0.6886	0.7097	0.7252	0.7097	0.6967
0.3393	6.0	96	0.4568	0.8387	0.8391	0.8387	0.8380
0.1909	7.0	112	0.4239	0.8387	0.8391	0.8387	0.8380
0.243	8.0	128	0.4323	0.8387	0.8391	0.8387	0.8380

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1