xnli_xlm_r_only_de

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

• Loss: 0.7212
• Accuracy: 0.7863

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: 128
• eval_batch_size: 128
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss
0.6876	1.0	3068	0.7671	0.5670
0.5323	2.0	6136	0.7972	0.5189
0.4652	3.0	9204	0.7928	0.5346
0.4089	4.0	12272	0.7940	0.5392
0.3614	5.0	15340	0.8092	0.5477
0.3173	6.0	18408	0.7920	0.6186
0.2805	7.0	21476	0.7936	0.6323
0.2496	8.0	24544	0.7960	0.6574
0.2246	9.0	27612	0.6894	0.7880
0.2068	10.0	30680	0.7212	0.7863

Framework versions

• Transformers 4.24.0
• Pytorch 1.13.0
• Datasets 2.6.1
• Tokenizers 0.13.1