transformers pytorch bert text-classification generated_from_trainer dataset:xnli license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- xnli
license: apache-2.0
metrics:
- accuracy
tags:
- text-classification
- generated_from_trainer
model-index:
- name: xnli_m_bert_only_el
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: xnli
      type: xnli
      config: el
      split: train
      args: el
    metrics:
    - type: accuracy
      value: 0.7433734939759036
      name: Accuracy
---

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# xnli_m_bert_only_el

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: 1.2248
- Accuracy: 0.7434

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6802        | 1.0   | 3068  | 0.7046          | 0.6968   |
| 0.6029        | 2.0   | 6136  | 0.6539          | 0.7317   |
| 0.5235        | 3.0   | 9204  | 0.6539          | 0.7281   |
| 0.4465        | 4.0   | 12272 | 0.6684          | 0.7353   |
| 0.3713        | 5.0   | 15340 | 0.7089          | 0.7470   |
| 0.2982        | 6.0   | 18408 | 0.8163          | 0.7406   |
| 0.2334        | 7.0   | 21476 | 0.8506          | 0.7478   |
| 0.1798        | 8.0   | 24544 | 0.9669          | 0.7434   |
| 0.1377        | 9.0   | 27612 | 1.1195          | 0.7446   |
| 0.1053        | 10.0  | 30680 | 1.2248          | 0.7434   |


### Framework versions

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