ToBeAndNotToBe
Collection
Datasets and models associated with the paper "To be and not to be: that is the question"
• 21 items • Updated
clasificador-ser-estar
This model is a fine-tuned version of google-bert/bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3110
- Accuracy: 0.9064
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 |
|---|---|---|---|---|
| No log | 1.0 | 77 | 0.3969 | 0.9064 |
| No log | 2.0 | 154 | 0.3107 | 0.9064 |
| No log | 3.0 | 231 | 0.3110 | 0.9064 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for joheras/clasificador-ser-estar
Base model
google-bert/bert-base-multilingual-uncased