Analisis-sentimientos-XLM-Roberta-TASS-C
This model is a fine-tuned version of cardiffnlp/twitter-xlm-roberta-base-sentiment on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.9503
- F1-score: 0.6139
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 | F1-score |
|---|---|---|---|---|
| 0.9136 | 1.0 | 241 | 0.8427 | 0.6223 |
| 0.6957 | 2.0 | 482 | 0.9260 | 0.6046 |
| 0.4825 | 3.0 | 723 | 1.1533 | 0.6004 |
| 0.299 | 4.0 | 964 | 1.2836 | 0.5952 |
| 0.2142 | 5.0 | 1205 | 1.5988 | 0.6160 |
| 0.1312 | 6.0 | 1446 | 2.5332 | 0.5879 |
| 0.0899 | 7.0 | 1687 | 2.4297 | 0.6233 |
| 0.0414 | 8.0 | 1928 | 2.7368 | 0.6129 |
| 0.023 | 9.0 | 2169 | 2.9262 | 0.6160 |
| 0.0203 | 10.0 | 2410 | 2.9503 | 0.6139 |
Framework versions
- Transformers 4.43.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
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