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distilbert-base-uncased-finetuned-subreddit_classification
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: 0.2958
- Accuracy: 0.91
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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.4142 | 0.6 | 30 | 1.2653 | 0.45 |
0.9856 | 1.2 | 60 | 0.7754 | 0.87 |
0.5056 | 1.8 | 90 | 0.4413 | 0.9 |
0.2248 | 2.4 | 120 | 0.2984 | 0.92 |
0.1352 | 3.0 | 150 | 0.3265 | 0.89 |
0.0856 | 3.6 | 180 | 0.2958 | 0.91 |
0.0715 | 4.2 | 210 | 0.2611 | 0.92 |
0.0615 | 4.8 | 240 | 0.2738 | 0.93 |
Framework versions
- Transformers 4.21.3
- Pytorch 1.13.0+cpu
- Datasets 2.8.0
- Tokenizers 0.12.1