metadata
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
model-index:
- name: xlm-roberta-large_emotion_ft_0416
results: []
xlm-roberta-large_emotion_ft_0416
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1186
- Accuracy: 0.9415
- F1: 0.9417
- Precision: 0.9177
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision |
|---|---|---|---|---|---|---|
| 0.8152 | 1.0 | 250 | 0.2905 | 0.902 | 0.9035 | 0.8660 |
| 0.215 | 2.0 | 500 | 0.1572 | 0.941 | 0.9409 | 0.9213 |
| 0.1274 | 3.0 | 750 | 0.1237 | 0.9445 | 0.9453 | 0.9075 |
| 0.101 | 4.0 | 1000 | 0.1186 | 0.9415 | 0.9417 | 0.9177 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3