---
license: mit
base_model: xlnet-large-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlnet-large-cased-detect-dep-v5
  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-large-cased-detect-dep-v5

This model is a fine-tuned version of [xlnet-large-cased](https://huggingface.co/xlnet-large-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5925
- Accuracy: 0.73
- F1: 0.7991

## 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: 5e-06
- 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 | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.6442        | 1.0   | 751  | 0.5586          | 0.733    | 0.8150 |
| 0.6032        | 2.0   | 1502 | 0.5649          | 0.743    | 0.8163 |
| 0.5574        | 3.0   | 2253 | 0.5397          | 0.754    | 0.8148 |
| 0.5368        | 4.0   | 3004 | 0.6118          | 0.727    | 0.8062 |
| 0.5123        | 5.0   | 3755 | 0.5925          | 0.73     | 0.7991 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3