Analisis-sentimientos-XLM-Roberta-TASS
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: 2.9837
- Rmse: 0.7071
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: 4
- 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 | Rmse |
---|---|---|---|---|
1.0334 | 1.0 | 156 | 0.9397 | 0.9439 |
0.7612 | 2.0 | 312 | 1.1421 | 0.7250 |
0.5843 | 3.0 | 468 | 1.5608 | 0.7026 |
0.2322 | 4.0 | 624 | 2.1870 | 0.6554 |
0.143 | 5.0 | 780 | 2.3847 | 0.7553 |
0.0953 | 6.0 | 936 | 2.3580 | 0.6841 |
0.027 | 7.0 | 1092 | 2.7096 | 0.6980 |
0.0103 | 8.0 | 1248 | 3.0068 | 0.7161 |
0.007 | 9.0 | 1404 | 2.9551 | 0.7026 |
0.0045 | 10.0 | 1560 | 2.9837 | 0.7071 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.13.3
- Downloads last month
- 14
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.