ECBERT-base-mlm
This model is a pretrained version of answerdotai/ModernBERT-base on 25,581 texts (available here) using MLM but not yet fine-tuned on the monetary policy sentiment analysis task. The best model achieves the following results on an out-of-sample test set (Graimond/ECBERT-idioms-dataset):
- Accuracy: 40.00%
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
- Training data: Graimond/ECBERT-mlm-dataset
- Evaluation data: Graimond/ECBERT-idioms-dataset
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-5
- weight_decay=0.01
- per_device_train_batch_size=16
- seed: 42
- epochs: 20
Training results
| Epoch | Training Loss | Validation Loss |
|---|---|---|
| 1 | 1.905000 | 1.903329 |
| 2 | 1.689700 | 1.764568 |
| 3 | 1.600900 | nan |
| 4 | 1.476500 | 1.683352 |
| 5 | 1.381200 | 1.629597 |
| 6 | 1.367300 | nan |
| 7 | 1.230300 | 1.628195 |
| 8 | 1.142700 | 1.567721 |
| 9 | 1.131800 | 1.618517 |
| 10 | 1.139700 | nan |
| 11 | 1.086200 | nan |
| 12 | 1.072500 | 1.560426 |
| 13 | 0.984800 | 1.556072 |
| 14 | 0.958500 | 1.606674 |
| 15 | 0.955600 | 1.619744 |
| 16 | 0.920500 | 1.581421 |
| 17 | 0.882300 | 1.535872 |
| 18 | 0.877900 | 1.565936 |
| 19 | 0.803100 | nan |
| 20 | 0.815700 | 1.604986 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0