metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: toxigen-distilbert-binary-clsf
results: []
datasets:
- toxigen/toxigen-data
language:
- en
pipeline_tag: text-classification
toxigen-distilbert-binary-clsf
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0001
- Precision: 0.9999
- Recall: 0.9999
- Accuracy: 0.9999
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: 64
- eval_batch_size: 64
- 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 | Precision | Recall | Accuracy |
|---|---|---|---|---|---|---|
| 0.0 | 1.0 | 3137 | 0.0001 | 0.9999 | 0.9999 | 0.9999 |
| 0.0 | 2.0 | 6274 | 0.0001 | 0.9999 | 0.9999 | 0.9999 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1