distilbert-base-uncased-finetuned-yahd-twval
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.2540
- Accuracy: 0.2664
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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.1967 | 1.0 | 10086 | 2.9662 | 0.2068 |
1.865 | 2.0 | 20172 | 2.9499 | 0.3229 |
1.5135 | 3.0 | 30258 | 3.3259 | 0.3036 |
1.2077 | 4.0 | 40344 | 3.8351 | 0.2902 |
1.0278 | 5.0 | 50430 | 4.2540 | 0.2664 |
Framework versions
- Transformers 4.12.3
- Pytorch 1.9.0+cu102
- Datasets 1.15.1
- Tokenizers 0.10.3
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