---
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
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# 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: 0.2964
- Rmse: 0.2828
- Accuracy: 0.92
- Precision: 0.9236
- Recall: 0.9329
- F1: 0.9282

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|:------:|
| 0.3798        | 1.0   | 1075 | 0.2964          | 0.2828 | 0.92     | 0.9236    | 0.9329 | 0.9282 |
| 0.2507        | 2.0   | 2150 | 0.3791          | 0.2973 | 0.9116   | 0.8824    | 0.9698 | 0.9241 |
| 0.1734        | 3.0   | 3225 | 0.3779          | 0.3080 | 0.9051   | 0.8847    | 0.9530 | 0.9176 |
| 0.1157        | 4.0   | 4300 | 0.4796          | 0.2861 | 0.9181   | 0.9456    | 0.9044 | 0.9245 |
| 0.0762        | 5.0   | 5375 | 0.4729          | 0.2762 | 0.9237   | 0.9341    | 0.9279 | 0.9310 |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1