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m-aliabbas1/roberta_en_med_1

sourceHugging Facemitupdated 1y agoView on Hugging Face

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robertaenmed_1

This model is a fine-tuned version of FacebookAI/roberta-base on the None dataset. It achieves the following results on the evaluation set:

—Loss: 0.7481
—F1: 0.8553
—Accuracy: 0.8567

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: 0.0001
—trainbatchsize: 64
—evalbatchsize: 32
—seed: 42
—optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
—lrschedulertype: linear
—num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
0.5726	1.0	1481	0.5461	0.8179	0.8218
0.495	2.0	2962	0.4922	0.8318	0.8332
0.3949	3.0	4443	0.4744	0.8421	0.8456
0.3627	4.0	5924	0.4744	0.8488	0.8502
0.3059	5.0	7405	0.4784	0.8509	0.8514
0.2555	6.0	8886	0.5150	0.8508	0.8522
0.2153	7.0	10367	0.5379	0.8462	0.8464
0.1657	8.0	11848	0.5893	0.8505	0.8514
0.1398	9.0	13329	0.6250	0.8476	0.8506
0.1067	10.0	14810	0.6537	0.8521	0.8522
0.0877	11.0	16291	0.7481	0.8553	0.8567
0.0582	12.0	17772	0.7734	0.8530	0.8538
0.0477	13.0	19253	0.8727	0.8524	0.8543
0.0349	14.0	20734	0.9370	0.8547	0.8561
0.0225	15.0	22215	0.9537	0.8549	0.8561

Framework versions

—Transformers 4.56.1
—Pytorch 2.4.1+cu124
—Datasets 4.0.0
—Tokenizers 0.22.0