mdeberta-v3-base-finetuned-pos
This model is a fine-tuned version of microsoft/mdeberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0887
- Acc: 0.9814
- F1: 0.8861
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 | Acc | F1 |
---|---|---|---|---|---|
No log | 1.0 | 439 | 0.0965 | 0.9749 | 0.8471 |
0.3317 | 2.0 | 878 | 0.0815 | 0.9783 | 0.8702 |
0.0775 | 3.0 | 1317 | 0.0780 | 0.9812 | 0.8825 |
0.0568 | 4.0 | 1756 | 0.0769 | 0.9809 | 0.8827 |
0.0444 | 5.0 | 2195 | 0.0799 | 0.9811 | 0.8885 |
0.0339 | 6.0 | 2634 | 0.0834 | 0.9813 | 0.8821 |
0.0278 | 7.0 | 3073 | 0.0845 | 0.9817 | 0.8843 |
0.0222 | 8.0 | 3512 | 0.0866 | 0.9814 | 0.8863 |
0.0222 | 9.0 | 3951 | 0.0885 | 0.9814 | 0.8862 |
0.0188 | 10.0 | 4390 | 0.0887 | 0.9814 | 0.8861 |
Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
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