metadata
license: mit
tags:
- text-classification
- generated_from_trainer
datasets:
- paws-x
metrics:
- accuracy
model-index:
- name: paws_x_xlm_r_only_es
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: paws-x
type: paws-x
config: es
split: train
args: es
metrics:
- name: Accuracy
type: accuracy
value: 0.8995
paws_x_xlm_r_only_es
This model is a fine-tuned version of xlm-roberta-base on the paws-x dataset. It achieves the following results on the evaluation set:
- Loss: 0.4565
- Accuracy: 0.8995
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 |
|---|---|---|---|---|
| 0.4688 | 1.0 | 386 | 0.3226 | 0.87 |
| 0.2192 | 2.0 | 772 | 0.3058 | 0.8895 |
| 0.1616 | 3.0 | 1158 | 0.2904 | 0.8955 |
| 0.125 | 4.0 | 1544 | 0.3465 | 0.898 |
| 0.1027 | 5.0 | 1930 | 0.3171 | 0.8955 |
| 0.0837 | 6.0 | 2316 | 0.4022 | 0.896 |
| 0.0716 | 7.0 | 2702 | 0.3625 | 0.9005 |
| 0.0613 | 8.0 | 3088 | 0.4102 | 0.898 |
| 0.052 | 9.0 | 3474 | 0.4257 | 0.8985 |
| 0.0441 | 10.0 | 3860 | 0.4565 | 0.8995 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1