metadata
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: language_detector
results: []
language_detector
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0157
- Accuracy: 0.9986
- F1 Macro: 0.9985
- Precision Macro: 0.9988
- Recall Macro: 0.9981
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro |
|---|---|---|---|---|---|---|---|
| 0.0207 | 1.0 | 3850 | 0.0094 | 0.9989 | 0.9987 | 0.9990 | 0.9985 |
| 0.007 | 2.0 | 7700 | 0.0141 | 0.9984 | 0.9982 | 0.9983 | 0.9981 |
| 0.0031 | 3.0 | 11550 | 0.0095 | 0.9993 | 0.9992 | 0.9995 | 0.999 |
| 0.0083 | 4.0 | 15400 | 0.0061 | 0.9995 | 0.9995 | 0.9997 | 0.9993 |
| 0.0013 | 5.0 | 19250 | 0.0157 | 0.9986 | 0.9985 | 0.9988 | 0.9981 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1