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shanhy/xlm-roberta-base_latin_kin-amh-eng_train_loss

sourceHugging Facemitupdated 3y agoView on Hugging Face

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xlm-roberta-baselatinkin-amh-engtrainloss

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

—Loss: 0.0326
—Spearman Corr: 0.7395

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: 128
—seed: 42
—gradientaccumulationsteps: 2
—totaltrainbatch_size: 64
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: linear
—num_epochs: 30
—mixedprecisiontraining: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Spearman Corr
No log	0.59	200	0.0303	0.6125
No log	1.17	400	0.0269	0.6780
No log	1.76	600	0.0393	0.6855
0.036	2.35	800	0.0338	0.7111
0.036	2.93	1000	0.0303	0.6886
0.036	3.52	1200	0.0327	0.7025
0.0243	4.11	1400	0.0269	0.7220
0.0243	4.69	1600	0.0287	0.7246
0.0243	5.28	1800	0.0260	0.7336
0.0243	5.87	2000	0.0266	0.7234
0.0185	6.45	2200	0.0252	0.7347
0.0185	7.04	2400	0.0281	0.7276
0.0185	7.62	2600	0.0294	0.7298
0.0141	8.21	2800	0.0274	0.7219
0.0141	8.8	3000	0.0285	0.7260
0.0141	9.38	3200	0.0276	0.7315
0.0141	9.97	3400	0.0291	0.7329
0.0109	10.56	3600	0.0310	0.7339
0.0109	11.14	3800	0.0326	0.7395

Framework versions

—Transformers 4.37.2
—Pytorch 2.2.0+cu121
—Datasets 2.17.0
—Tokenizers 0.15.2