MeMo_BERT-01
This model is a fine-tuned version of MiMe-MeMo/MeMo_BERT-01 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.8264
- F1-score: 0.4148
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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | F1-score |
|---|---|---|---|---|
| No log | 1.0 | 61 | 1.5574 | 0.1229 |
| No log | 2.0 | 122 | 1.4491 | 0.1477 |
| No log | 3.0 | 183 | 1.3661 | 0.2112 |
| No log | 4.0 | 244 | 1.7131 | 0.3356 |
| No log | 5.0 | 305 | 2.0026 | 0.3592 |
| No log | 6.0 | 366 | 2.8807 | 0.2263 |
| No log | 7.0 | 427 | 2.8357 | 0.3625 |
| No log | 8.0 | 488 | 3.5272 | 0.3150 |
| 0.7496 | 9.0 | 549 | 3.5185 | 0.3402 |
| 0.7496 | 10.0 | 610 | 3.8264 | 0.4148 |
| 0.7496 | 11.0 | 671 | 4.5875 | 0.2999 |
| 0.7496 | 12.0 | 732 | 4.3188 | 0.3392 |
| 0.7496 | 13.0 | 793 | 4.7118 | 0.3098 |
| 0.7496 | 14.0 | 854 | 4.5895 | 0.3319 |
| 0.7496 | 15.0 | 915 | 4.6764 | 0.3033 |
| 0.7496 | 16.0 | 976 | 4.6250 | 0.3319 |
| 0.01 | 17.0 | 1037 | 4.7393 | 0.3176 |
| 0.01 | 18.0 | 1098 | 4.7690 | 0.3176 |
| 0.01 | 19.0 | 1159 | 4.7655 | 0.3176 |
| 0.01 | 20.0 | 1220 | 4.7695 | 0.3176 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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