distilbert-base-uncased-finetuned-toxicity
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0086
- Accuracy: 0.999
- F1: 0.9990
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: 8.589778712669143e-05
- train_batch_size: 400
- eval_batch_size: 400
- 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 | F1 |
---|---|---|---|---|---|
No log | 1.0 | 20 | 0.0142 | 0.998 | 0.998 |
No log | 2.0 | 40 | 0.0112 | 0.997 | 0.9970 |
No log | 3.0 | 60 | 0.0088 | 0.999 | 0.9990 |
No log | 4.0 | 80 | 0.0091 | 0.998 | 0.998 |
No log | 5.0 | 100 | 0.0086 | 0.999 | 0.9990 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.1
- Datasets 2.0.0
- Tokenizers 0.11.0
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