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amazon_massive_intent-en-US-distilbert
This model is a fine-tuned version of distilbert-base-uncased on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.7769
- Accuracy: 0.8869
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: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.1629 | 1.0 | 720 | 0.9624 | 0.7959 |
0.7179 | 2.0 | 1440 | 0.5693 | 0.8569 |
0.3695 | 3.0 | 2160 | 0.5104 | 0.8692 |
0.2227 | 4.0 | 2880 | 0.4813 | 0.8888 |
0.1302 | 5.0 | 3600 | 0.5207 | 0.8834 |
0.0822 | 6.0 | 4320 | 0.5709 | 0.8829 |
0.0527 | 7.0 | 5040 | 0.6016 | 0.8854 |
0.0345 | 8.0 | 5760 | 0.6373 | 0.8839 |
0.0244 | 9.0 | 6480 | 0.6616 | 0.8908 |
0.0191 | 10.0 | 7200 | 0.6958 | 0.8854 |
0.0131 | 11.0 | 7920 | 0.7212 | 0.8844 |
0.0095 | 12.0 | 8640 | 0.7348 | 0.8864 |
0.0067 | 13.0 | 9360 | 0.7502 | 0.8824 |
0.0055 | 14.0 | 10080 | 0.7469 | 0.8819 |
0.0038 | 15.0 | 10800 | 0.7772 | 0.8854 |
0.0043 | 16.0 | 11520 | 0.7761 | 0.8844 |
0.0025 | 17.0 | 12240 | 0.7625 | 0.8893 |
0.002 | 18.0 | 12960 | 0.7782 | 0.8854 |
0.0014 | 19.0 | 13680 | 0.7867 | 0.8859 |
0.0019 | 20.0 | 14400 | 0.7769 | 0.8869 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3