metadata
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: XLNet-Reddit-Toxic-Comment-Classification
results: []
XLNet-Reddit-Toxic-Comment-Classification
This model is a fine-tuned version of xlnet-base-cased on the Toxic Comment Classification Challenge dataset. It achieves the following results on the evaluation set:
- Loss: 0.2615
- Rmse: 0.2748
- Accuracy: 0.9245
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 | Rmse | Accuracy |
|---|---|---|---|---|---|
| 0.3672 | 1.0 | 1073 | 0.2615 | 0.2748 | 0.9245 |
| 0.2441 | 2.0 | 2146 | 0.3464 | 0.2896 | 0.9161 |
| 0.1726 | 3.0 | 3219 | 0.3880 | 0.2661 | 0.9292 |
| 0.1146 | 4.0 | 4292 | 0.3287 | 0.2499 | 0.9376 |
| 0.0831 | 5.0 | 5365 | 0.3672 | 0.2590 | 0.9329 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1