---
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: XLNet-Reddit-Sentiment-Analysis-16-epochs
  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-Sentiment-Analysis-16-epochs

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: 0.7667
- Rmse: 0.6675
- Accuracy: 0.8427

## 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: 9

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rmse   | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:--------:|
| 0.8682        | 1.0   | 3790  | 0.7667          | 0.6675 | 0.8427   |
| 0.736         | 2.0   | 7580  | 0.7681          | 0.6234 | 0.8585   |
| 0.7613        | 3.0   | 11370 | 0.8174          | 0.6668 | 0.8405   |
| 0.9229        | 4.0   | 15160 | 1.2618          | 0.8202 | 0.6568   |
| 1.0546        | 5.0   | 18950 | 1.2372          | 0.7880 | 0.7592   |
| 0.9142        | 6.0   | 22740 | 0.9488          | 0.7339 | 0.8163   |
| 0.8341        | 7.0   | 26530 | 0.8846          | 0.7230 | 0.8194   |
| 0.8028        | 8.0   | 30320 | 0.8510          | 0.7030 | 0.8289   |
| 0.7784        | 9.0   | 34110 | 0.8805          | 0.7060 | 0.8279   |


### Framework versions

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