---
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: task1_xlnet-base-cased_3_4_2e-05_0.01
  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. -->

# task1_xlnet-base-cased_3_4_2e-05_0.01

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: 0.3630
- Accuracy: 0.9447
- F1: 0.8571
- Precision: 0.8219
- Recall: 0.8955

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.3153        | 1.0   | 1629 | 0.2537          | 0.9336   | 0.8356 | 0.7722    | 0.9104 |
| 0.1964        | 2.0   | 3258 | 0.3178          | 0.9392   | 0.8413 | 0.8140    | 0.8706 |
| 0.0756        | 3.0   | 4887 | 0.3630          | 0.9447   | 0.8571 | 0.8219    | 0.8955 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3