---
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: xlnet-base-cased-tweets
  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-base-cased-tweets

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: 0.2094
- Accuracy: 0.9236
- F1: 0.9553
- Precision: 0.9531
- Recall: 0.9575

## 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: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2551        | 1.0   | 642  | 0.2172          | 0.9037   | 0.9443 | 0.9311    | 0.9579 |
| 0.1981        | 2.0   | 1284 | 0.2366          | 0.9135   | 0.9500 | 0.9349    | 0.9657 |
| 0.1513        | 3.0   | 1926 | 0.2094          | 0.9236   | 0.9553 | 0.9531    | 0.9575 |


### Framework versions

- Transformers 4.43.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1