---
license: mit
tags:
- generated_from_trainer
datasets:
- sentiment140
metrics:
- accuracy
model-index:
- name: Sentiment140_XLNET_5E
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: sentiment140
      type: sentiment140
      config: sentiment140
      split: train
      args: sentiment140
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.84
---

<!-- 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. -->

# Sentiment140_XLNET_5E

This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the sentiment140 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3797
- Accuracy: 0.84

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6687        | 0.08  | 50   | 0.5194          | 0.76     |
| 0.5754        | 0.16  | 100  | 0.4500          | 0.7867   |
| 0.5338        | 0.24  | 150  | 0.3725          | 0.8333   |
| 0.5065        | 0.32  | 200  | 0.4093          | 0.8133   |
| 0.4552        | 0.4   | 250  | 0.3910          | 0.8267   |
| 0.5352        | 0.48  | 300  | 0.3888          | 0.82     |
| 0.415         | 0.56  | 350  | 0.3887          | 0.8267   |
| 0.4716        | 0.64  | 400  | 0.3888          | 0.84     |
| 0.4565        | 0.72  | 450  | 0.3619          | 0.84     |
| 0.4447        | 0.8   | 500  | 0.3758          | 0.8333   |
| 0.4407        | 0.88  | 550  | 0.3664          | 0.8133   |
| 0.46          | 0.96  | 600  | 0.3797          | 0.84     |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.3.2
- Tokenizers 0.13.1