---
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fact_test_with_xlnet
  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. -->

# fact_test_with_xlnet

This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co./xlnet-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6043
- Accuracy: 0.672

## 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-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 310  | 0.9194          | 0.66     |
| 0.9336        | 2.0   | 620  | 0.8339          | 0.696    |
| 0.9336        | 3.0   | 930  | 1.1543          | 0.702    |
| 0.3955        | 4.0   | 1240 | 1.4356          | 0.682    |
| 0.1551        | 5.0   | 1550 | 1.6043          | 0.672    |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2