---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# XLNet-Reddit-Toxic-Comment-Classification

This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/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