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Hina541/fineTuningXLMRoberta-TokenClassification-latest

sourceHugging Faceupdated 2y agoView on Hugging Face

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fineTuningXLMRoberta-TokenClassification-latest

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

—Loss: 0.8366
—Precision: 0.1689
—Recall: 0.1683
—F1: 0.1686
—Accuracy: 0.6766

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
—trainbatchsize: 32
—evalbatchsize: 32
—seed: 42
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: linear
—num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	33	0.7181	0.1472	0.1219	0.1333	0.6725
No log	2.0	66	0.7405	0.1414	0.1644	0.1521	0.6716
No log	3.0	99	0.6809	0.1694	0.1393	0.1529	0.6976
No log	4.0	132	0.7435	0.1216	0.1393	0.1298	0.6450
No log	5.0	165	0.7392	0.1709	0.1431	0.1558	0.6904
No log	6.0	198	0.7356	0.1768	0.1741	0.1754	0.6880
No log	7.0	231	0.7665	0.1699	0.1683	0.1691	0.6841
No log	8.0	264	0.7958	0.1540	0.1683	0.1608	0.6537
No log	9.0	297	0.8161	0.1607	0.1567	0.1587	0.6742
No log	10.0	330	0.8132	0.1776	0.1721	0.1749	0.6778
No log	11.0	363	0.8387	0.1617	0.1663	0.1640	0.6672
No log	12.0	396	0.8290	0.1770	0.1760	0.1765	0.6795
No log	13.0	429	0.8456	0.1770	0.1760	0.1765	0.6750
No log	14.0	462	0.8377	0.1692	0.1702	0.1697	0.6762
No log	15.0	495	0.8366	0.1689	0.1683	0.1686	0.6766

Framework versions

—Transformers 4.44.0
—Pytorch 2.4.0
—Datasets 2.21.0
—Tokenizers 0.19.1