---
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_trainer
datasets:
- tweet_sentiment_multilingual
metrics:
- accuracy
model-index:
- name: xlnet-finetuned-socialmediatweet
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: tweet_sentiment_multilingual
      type: tweet_sentiment_multilingual
      config: english
      split: validation
      args: english
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7129629850387573
---

<!-- 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-finetuned-socialmediatweet

This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the tweet_sentiment_multilingual dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6923
- Accuracy: 0.7130

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0161        | 1.0   | 58   | 2.4538          | 0.6821   |
| 0.0416        | 2.0   | 116  | 2.3751          | 0.6821   |
| 0.0294        | 3.0   | 174  | 2.4929          | 0.7068   |
| 0.031         | 4.0   | 232  | 2.5655          | 0.7037   |
| 0.0422        | 5.0   | 290  | 3.0881          | 0.6605   |
| 0.0751        | 6.0   | 348  | 2.6787          | 0.6883   |
| 0.0264        | 7.0   | 406  | 2.5283          | 0.7006   |
| 0.0123        | 8.0   | 464  | 2.5634          | 0.7006   |
| 0.0277        | 9.0   | 522  | 2.7127          | 0.6852   |
| 0.0448        | 10.0  | 580  | 2.6113          | 0.6759   |
| 0.0261        | 11.0  | 638  | 2.6640          | 0.6759   |
| 0.0111        | 12.0  | 696  | 2.6089          | 0.6914   |
| 0.0239        | 13.0  | 754  | 2.5785          | 0.6975   |
| 0.0255        | 14.0  | 812  | 2.6923          | 0.7130   |
| 0.0242        | 15.0  | 870  | 2.4704          | 0.7068   |
| 0.0131        | 16.0  | 928  | 2.6724          | 0.6667   |
| 0.0059        | 17.0  | 986  | 2.5554          | 0.7068   |
| 0.0066        | 18.0  | 1044 | 2.6696          | 0.6698   |
| 0.001         | 19.0  | 1102 | 2.5653          | 0.6883   |
| 0.0026        | 20.0  | 1160 | 2.5846          | 0.6883   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0