distilbert-base-uncased-finetuned-sst-2-english_Toxic_comment_detector
This model is a fine-tuned version of distilbert/distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3017
- Accuracy: 0.9399
- Precision: 0.9400
- Recall: 0.9399
- F1: 0.9399
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: 1.9355557817465813e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.1885 | 1.0 | 2640 | 0.1904 | 0.9403 | 0.9407 | 0.9403 | 0.9403 |
0.1176 | 2.0 | 5280 | 0.2532 | 0.9408 | 0.9409 | 0.9408 | 0.9408 |
0.058 | 3.0 | 7920 | 0.3017 | 0.9399 | 0.9400 | 0.9399 | 0.9399 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Downloads last month
- 16
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
๐
Ask for provider support