metadata
library_name: peft
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: emotion-model11_0
results: []
emotion-model11_0
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0583
- Accuracy: 0.5828
- F1: 0.5244
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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 41 | 1.3349 | 0.3804 | 0.2096 |
| 1.3438 | 2.0 | 82 | 1.2443 | 0.3804 | 0.2096 |
| 1.2717 | 3.0 | 123 | 1.0583 | 0.5828 | 0.5244 |
| 1.1723 | 4.0 | 164 | 1.0449 | 0.5215 | 0.3965 |
| 1.1136 | 5.0 | 205 | 0.9935 | 0.5521 | 0.4423 |
| 1.1136 | 6.0 | 246 | 0.9746 | 0.5890 | 0.5003 |
| 1.1124 | 7.0 | 287 | 0.9637 | 0.5890 | 0.5003 |
| 1.0842 | 8.0 | 328 | 0.9562 | 0.5767 | 0.4846 |
| 1.0456 | 9.0 | 369 | 0.9516 | 0.5767 | 0.4837 |
| 1.0552 | 10.0 | 410 | 0.9428 | 0.5767 | 0.4837 |
Framework versions
- PEFT 0.15.2
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1