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

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: 0.7135
- Rmse: 0.6123
- Accuracy: 0.8691

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:--------:|
| 0.8907        | 1.0   | 3790  | 0.9401          | 0.6715 | 0.8152   |
| 0.7855        | 2.0   | 7580  | 0.7974          | 0.6301 | 0.8501   |
| 0.6837        | 3.0   | 11370 | 0.8520          | 0.6384 | 0.8553   |
| 0.6271        | 4.0   | 15160 | 0.7731          | 0.6140 | 0.8669   |
| 0.5311        | 5.0   | 18950 | 0.7135          | 0.6123 | 0.8691   |


### Framework versions

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