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da-sentiment
This model is a fine-tuned version of Maltehb/danish-bert-botxo on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4976
- Accuracy: 0.8377
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 58 | 0.6168 | 0.7446 |
| No log | 2.0 | 116 | 0.5689 | 0.7554 |
| 0.4255 | 3.0 | 174 | 0.5542 | 0.7814 |
| 0.4255 | 4.0 | 232 | 0.5224 | 0.7944 |
| 0.2655 | 5.0 | 290 | 0.5172 | 0.8030 |
| 0.2655 | 6.0 | 348 | 0.4992 | 0.8182 |
| 0.1944 | 7.0 | 406 | 0.4852 | 0.8290 |
| 0.1944 | 8.0 | 464 | 0.4972 | 0.8312 |
| 0.1772 | 9.0 | 522 | 0.4905 | 0.8333 |
| 0.1772 | 10.0 | 580 | 0.4915 | 0.8290 |
| 0.1772 | 11.0 | 638 | 0.4936 | 0.8333 |
| 0.1654 | 12.0 | 696 | 0.4939 | 0.8333 |
| 0.1654 | 13.0 | 754 | 0.4944 | 0.8377 |
| 0.1605 | 14.0 | 812 | 0.4969 | 0.8355 |
| 0.1605 | 15.0 | 870 | 0.4976 | 0.8377 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
