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---
license: apache-2.0
tags:
- text-classification
- generated_from_trainer
datasets:
- xnli
metrics:
- accuracy
model-index:
- name: xnli_m_bert_only_es
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: xnli
type: xnli
config: es
split: train
args: es
metrics:
- name: Accuracy
type: accuracy
value: 0.7795180722891566
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xnli_m_bert_only_es
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the xnli dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1865
- Accuracy: 0.7795
## 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
- 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
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6124 | 1.0 | 3068 | 0.6275 | 0.7333 |
| 0.5209 | 2.0 | 6136 | 0.5399 | 0.7759 |
| 0.4244 | 3.0 | 9204 | 0.6163 | 0.7671 |
| 0.3365 | 4.0 | 12272 | 0.6123 | 0.7667 |
| 0.2594 | 5.0 | 15340 | 0.6834 | 0.7739 |
| 0.1901 | 6.0 | 18408 | 0.8212 | 0.7639 |
| 0.1419 | 7.0 | 21476 | 0.8601 | 0.7719 |
| 0.1023 | 8.0 | 24544 | 1.0357 | 0.7635 |
| 0.0751 | 9.0 | 27612 | 1.0908 | 0.7727 |
| 0.0541 | 10.0 | 30680 | 1.1865 | 0.7795 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1
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