my_segment_news_1
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: 1.3054
- Accuracy: 0.7046
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 | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 47 | 0.8568 | 0.6555 |
| No log | 2.0 | 94 | 0.7703 | 0.7128 |
| No log | 3.0 | 141 | 0.9174 | 0.7115 |
| No log | 4.0 | 188 | 0.9764 | 0.7268 |
| No log | 5.0 | 235 | 1.1855 | 0.6945 |
| No log | 6.0 | 282 | 1.1718 | 0.7071 |
| No log | 7.0 | 329 | 1.1631 | 0.7246 |
| No log | 8.0 | 376 | 1.2950 | 0.7029 |
| No log | 9.0 | 423 | 1.3254 | 0.7019 |
| No log | 10.0 | 470 | 1.3054 | 0.7046 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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