---
license: apache-2.0
tags:
- text-classification
- generated_from_trainer
datasets:
- xnli
metrics:
- accuracy
model-index:
- name: xnli_m_bert_only_en_single_gpu
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: xnli
      type: xnli
      config: en
      split: train
      args: en
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8076305220883534
---

<!-- 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_en_single_gpu

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: 1.0082
- Accuracy: 0.8076

## 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: 7

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3328        | 1.0   | 3068  | 0.5433          | 0.8036   |
| 0.259         | 2.0   | 6136  | 0.5708          | 0.8008   |
| 0.2023        | 3.0   | 9204  | 0.6475          | 0.8048   |
| 0.1362        | 4.0   | 12272 | 0.7661          | 0.7972   |
| 0.0945        | 5.0   | 15340 | 0.8333          | 0.8008   |
| 0.0665        | 6.0   | 18408 | 0.9312          | 0.8092   |
| 0.0463        | 7.0   | 21476 | 1.0082          | 0.8076   |


### Framework versions

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