distilbert-base-uncased-finetuned-yahd-twval-hptune
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: 6.3727
- Accuracy: 0.2039
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: 6e-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 |
---|---|---|---|---|
2.1638 | 1.0 | 10106 | 2.1944 | 0.3646 |
1.7982 | 2.0 | 20212 | 2.6390 | 0.3333 |
1.3279 | 3.0 | 30318 | 3.1526 | 0.3095 |
0.8637 | 4.0 | 40424 | 4.8368 | 0.2470 |
0.5727 | 5.0 | 50530 | 6.3727 | 0.2039 |
Framework versions
- Transformers 4.12.3
- Pytorch 1.9.0+cu102
- Datasets 1.15.1
- Tokenizers 0.10.3
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