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20230429-001-baseline-mbert-no-qa-ft-clickbait-spoiling
This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.9025
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: 2e-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: 10
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 1.0 | 200 | 3.3463 |
No log | 2.0 | 400 | 3.1131 |
3.2437 | 3.0 | 600 | 3.3240 |
3.2437 | 4.0 | 800 | 3.4426 |
1.6579 | 5.0 | 1000 | 3.8462 |
1.6579 | 6.0 | 1200 | 4.1288 |
1.6579 | 7.0 | 1400 | 4.4595 |
0.753 | 8.0 | 1600 | 4.6898 |
0.753 | 9.0 | 1800 | 4.8666 |
0.4008 | 10.0 | 2000 | 4.9025 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3