timelist_factchecker
This model is a fine-tuned version of EuroBERT/EuroBERT-610m on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.0285
- Accuracy: 0.5673
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: 3e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 375 | 3.1052 | 0.4776 |
| 1.6932 | 2.0 | 750 | 2.4263 | 0.5075 |
| 1.2145 | 3.0 | 1125 | 2.9333 | 0.5224 |
| 0.415 | 4.0 | 1500 | 3.1425 | 0.5672 |
| 0.415 | 5.0 | 1875 | 3.0285 | 0.5373 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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Model tree for athugodage/factchecker_v0
Base model
EuroBERT/EuroBERT-610m