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: 0.3448
- Rmse: 0.2976
- Accuracy: 0.9115
- Precision: 0.9153
- Recall: 0.9261
- F1: 0.9206
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 |
|---|---|---|---|---|---|---|---|---|
| 0.7011 | 1.0 | 1073 | 0.6911 | 0.6674 | 0.5545 | 0.5545 | 1.0 | 0.7134 |
| 0.6829 | 2.0 | 2146 | 0.6936 | 0.7447 | 0.4455 | 0.0 | 0.0 | 0.0 |
| 0.7004 | 3.0 | 3219 | 0.6876 | 0.6674 | 0.5545 | 0.5545 | 1.0 | 0.7134 |
| 0.5187 | 4.0 | 4292 | 0.3967 | 0.3202 | 0.8975 | 0.9117 | 0.9025 | 0.9071 |
| 0.3208 | 5.0 | 5365 | 0.3448 | 0.2976 | 0.9115 | 0.9153 | 0.9261 | 0.9206 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1