metadata
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
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 None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2248
- Rmse: 0.2928
- Accuracy: 0.9143
- Precision: 0.9299
- Recall: 0.9143
- F1: 0.9220
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 | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|---|
| 0.3656 | 1.0 | 1073 | 0.2248 | 0.2928 | 0.9143 | 0.9299 | 0.9143 | 0.9220 |
| 0.2432 | 2.0 | 2146 | 0.3105 | 0.2912 | 0.9152 | 0.9158 | 0.9328 | 0.9242 |
| 0.1649 | 3.0 | 3219 | 0.3818 | 0.2696 | 0.9273 | 0.9176 | 0.9546 | 0.9357 |
| 0.1075 | 4.0 | 4292 | 0.4398 | 0.2798 | 0.9217 | 0.9049 | 0.9597 | 0.9315 |
| 0.0788 | 5.0 | 5365 | 0.4655 | 0.2847 | 0.9189 | 0.9110 | 0.9462 | 0.9283 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1