memobert_NCS
This model is a fine-tuned version of MiMe-MeMo/MeMo-BERT-03 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4169
- F1-score: 0.8127
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 | F1-score |
---|---|---|---|---|
0.4805 | 1.0 | 504 | 0.4169 | 0.8127 |
0.3748 | 2.0 | 1008 | 0.4367 | 0.8110 |
0.2404 | 3.0 | 1512 | 0.5782 | 0.8112 |
0.1523 | 4.0 | 2016 | 0.8041 | 0.8061 |
0.0838 | 5.0 | 2520 | 1.0791 | 0.8007 |
0.047 | 6.0 | 3024 | 1.3892 | 0.7851 |
0.0314 | 7.0 | 3528 | 1.4142 | 0.7890 |
0.0171 | 8.0 | 4032 | 1.4453 | 0.7939 |
0.0096 | 9.0 | 4536 | 1.5124 | 0.7933 |
0.0103 | 10.0 | 5040 | 1.5355 | 0.7943 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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MiMe-MeMo/MeMo-BERT-03