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tsc-data-science/outputs

sourceHugging Facemitupdated 2y agoView on Hugging Face

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outputs

This model is a fine-tuned version of FacebookAI/xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

—Loss: 0.1489
—F1 Micro: 0.8209
—Precision Micro: 0.8209
—Recall Micro: 0.8209

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: 5e-05
—trainbatchsize: 8
—evalbatchsize: 8
—seed: 42
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: linear
—num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Micro	Precision Micro	Recall Micro
0.4507	0.7782	200	0.3227	0.0	0.0	0.0
0.263	1.5564	400	0.2081	0.5201	0.8744	0.3701
0.1789	2.3346	600	0.1686	0.7489	0.8231	0.6870
0.13	3.1128	800	0.1555	0.7691	0.8074	0.7343
0.1063	3.8911	1000	0.1416	0.7974	0.7649	0.8327
0.0844	4.6693	1200	0.1492	0.8	0.8008	0.7992
0.0617	5.4475	1400	0.1449	0.8268	0.8268	0.8268
0.0534	6.2257	1600	0.1388	0.8283	0.8258	0.8307
0.0352	7.0039	1800	0.1471	0.8272	0.8297	0.8248
0.0296	7.7821	2000	0.1489	0.8209	0.8209	0.8209

Framework versions

—Transformers 4.41.1
—Pytorch 2.1.0.post100
—Datasets 2.19.0
—Tokenizers 0.19.1