transformers pytorch bert text-classification generated_from_trainer dataset:paws-x license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- paws-x
license: apache-2.0
metrics:
- accuracy
tags:
- text-classification
- generated_from_trainer
model-index:
- name: paws_x_m_bert_only_en
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: paws-x
      type: paws-x
      config: en
      split: train
      args: en
    metrics:
    - type: accuracy
      value: 0.925
      name: Accuracy
---

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# paws_x_m_bert_only_en

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the paws-x dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4996
- Accuracy: 0.925

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3185        | 1.0   | 772  | 0.2330          | 0.916    |
| 0.1484        | 2.0   | 1544 | 0.2518          | 0.9205   |
| 0.1013        | 3.0   | 2316 | 0.2902          | 0.921    |
| 0.0735        | 4.0   | 3088 | 0.2797          | 0.9265   |
| 0.0544        | 5.0   | 3860 | 0.2789          | 0.9315   |
| 0.0406        | 6.0   | 4632 | 0.3514          | 0.929    |
| 0.0313        | 7.0   | 5404 | 0.3799          | 0.926    |
| 0.022         | 8.0   | 6176 | 0.4567          | 0.9255   |
| 0.0156        | 9.0   | 6948 | 0.4652          | 0.9275   |
| 0.0123        | 10.0  | 7720 | 0.4996          | 0.925    |


### Framework versions

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