bert-base-uncased-finetuned-MeIA-AnalisisDeSentimientos
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0784
- F1: 0.5207
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 1.1946 | 1.0 | 766 | 1.1920 | 0.4331 |
| 1.0715 | 2.0 | 1532 | 1.0936 | 0.4909 |
| 1.0093 | 3.0 | 2298 | 1.0583 | 0.5116 |
| 0.8907 | 4.0 | 3064 | 1.0784 | 0.5207 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3