distilbert-base-uncased-finetuned-ag_news
This model is a fine-tuned version of distilbert-base-uncased on the ag_news dataset. It achieves the following results on the evaluation set:
- Loss: 0.1691
- Accuracy: 0.9443
- F1: 0.9444
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: 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: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.2253 | 1.0 | 3750 | 0.1749 | 0.9411 | 0.9413 |
0.1335 | 2.0 | 7500 | 0.1691 | 0.9443 | 0.9444 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.1.0+cu121
- Datasets 1.16.1
- Tokenizers 0.15.0
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Dataset used to train TingTing0104/distilbert-base-uncased-finetuned-ag_news
Evaluation results
- Accuracy on ag_newsself-reported0.944
- F1 on ag_newsself-reported0.944