metadata
license: apache-2.0
tags:
- text-classification
- generated_from_trainer
datasets:
- paws-x
metrics:
- accuracy
base_model: bert-base-multilingual-cased
model-index:
- name: paws_x_m_bert_only_es
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: paws-x
type: paws-x
config: es
split: train
args: es
metrics:
- type: accuracy
value: 0.883
name: Accuracy
paws_x_m_bert_only_es
This model is a fine-tuned version of bert-base-multilingual-cased on the paws-x dataset. It achieves the following results on the evaluation set:
- Loss: 0.5894
- Accuracy: 0.883
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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4197 | 1.0 | 386 | 0.3860 | 0.843 |
| 0.2041 | 2.0 | 772 | 0.3299 | 0.8755 |
| 0.1389 | 3.0 | 1158 | 0.3597 | 0.88 |
| 0.1027 | 4.0 | 1544 | 0.3851 | 0.878 |
| 0.0779 | 5.0 | 1930 | 0.4119 | 0.8815 |
| 0.0631 | 6.0 | 2316 | 0.4387 | 0.8865 |
| 0.0517 | 7.0 | 2702 | 0.4643 | 0.888 |
| 0.0416 | 8.0 | 3088 | 0.4944 | 0.887 |
| 0.0364 | 9.0 | 3474 | 0.5478 | 0.8845 |
| 0.0297 | 10.0 | 3860 | 0.5894 | 0.883 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1