bert-xnli-es-classifier

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the xnli dataset. It achieves the following results on the evaluation set:

• Loss: 0.5109
• Accuracy: 0.8277

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: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4401	1.0	6136	0.4733	0.8116
0.4245	2.0	12272	0.4667	0.8309
0.29	3.0	18408	0.5109	0.8277

Framework versions

• Transformers 4.28.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3