clasificador-tweet-sentiment
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4368
- Accuracy: 0.6776
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6539 | 1.0 | 5702 | 0.6873 | 0.6923 |
| 0.4591 | 2.0 | 11404 | 0.8274 | 0.6751 |
| 0.2694 | 3.0 | 17106 | 1.4368 | 0.6776 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.2
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for el-filatova/clasificador-tweet-sentiment
Base model
google-bert/bert-base-uncased