---
license: mit
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: IMDB_XLNET_5E
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: imdb
      type: imdb
      config: plain_text
      split: train
      args: plain_text
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.94
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# IMDB_XLNET_5E

This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3195
- Accuracy: 0.94

## 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: 32
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3192        | 0.63  | 50   | 0.2033          | 0.94     |
| 0.196         | 1.27  | 100  | 0.2036          | 0.9467   |
| 0.1651        | 1.9   | 150  | 0.2106          | 0.9267   |
| 0.0628        | 2.53  | 200  | 0.3531          | 0.92     |
| 0.0865        | 3.16  | 250  | 0.2186          | 0.9533   |
| 0.0436        | 3.8   | 300  | 0.2718          | 0.9533   |
| 0.0254        | 4.43  | 350  | 0.3195          | 0.94     |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1