metadata
base_model: daveni/twitter-xlm-roberta-emotion-es
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: xml-roberta-HU-Com
results: []
xml-roberta-HU-Com
This model is a fine-tuned version of daveni/twitter-xlm-roberta-emotion-es on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3693
- Accuracy: 0.7911
- F1: 0.7440
- Precision: 0.7415
- Recall: 0.7466
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.6717 | 1.0 | 90 | 0.5918 | 0.6852 | 0.5272 | 0.6774 | 0.4315 |
| 0.453 | 2.0 | 180 | 0.5358 | 0.7465 | 0.6403 | 0.7570 | 0.5548 |
| 0.2631 | 3.0 | 270 | 0.7088 | 0.7744 | 0.7273 | 0.7152 | 0.7397 |
| 0.1936 | 4.0 | 360 | 0.7078 | 0.7939 | 0.7566 | 0.7278 | 0.7877 |
| 0.1273 | 5.0 | 450 | 1.1057 | 0.7772 | 0.7436 | 0.6988 | 0.7945 |
| 0.066 | 6.0 | 540 | 1.1990 | 0.7799 | 0.7168 | 0.7519 | 0.6849 |
| 0.0286 | 7.0 | 630 | 1.2457 | 0.7994 | 0.7584 | 0.7434 | 0.7740 |
| 0.0261 | 8.0 | 720 | 1.3297 | 0.7799 | 0.7106 | 0.7638 | 0.6644 |
| 0.0097 | 9.0 | 810 | 1.3733 | 0.7855 | 0.7354 | 0.7379 | 0.7329 |
| 0.0071 | 10.0 | 900 | 1.3693 | 0.7911 | 0.7440 | 0.7415 | 0.7466 |
Framework versions
- Transformers 4.43.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1