---
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: baseline_xlnet-base-cased_epoch2_batch2_lr2e-05_w0.01
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# baseline_xlnet-base-cased_epoch2_batch2_lr2e-05_w0.01

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: 0.5189
- Accuracy: 0.8854
- F1: 0.8442
- Precision: 0.8558
- Recall: 0.8328

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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.7846        | 1.0   | 1575 | 0.6591          | 0.8343   | 0.7453 | 0.872     | 0.6507 |
| 0.536         | 2.0   | 3150 | 0.5189          | 0.8854   | 0.8442 | 0.8558    | 0.8328 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3