transformers pytorch xlm-roberta text-classification generated_from_trainer dataset:tweet_sentiment_multilingual base_model:facebook/xlm-v-base base_model:finetune:facebook/xlm-v-base license:mit model-index autotrain_compatible endpoints_compatible region:us
---
base_model: facebook/xlm-v-base
datasets:
- tweet_sentiment_multilingual
license: mit
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_alpha2
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: tweet_sentiment_multilingual
      type: tweet_sentiment_multilingual
      config: all
      split: validation
      args: all
    metrics:
    - type: accuracy
      value: 0.3333333333333333
      name: Accuracy
    - type: f1
      value: 0.16666666666666666
      name: F1
---

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# scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_alpha2

This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface.co/facebook/xlm-v-base) on the tweet_sentiment_multilingual dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0987
- Accuracy: 0.3333
- F1: 0.1667

## 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: 32
- eval_batch_size: 32
- seed: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.1001        | 1.09  | 500  | 1.0987          | 0.3333   | 0.1667 |
| 1.0999        | 2.17  | 1000 | 1.0990          | 0.3333   | 0.1667 |
| 1.0998        | 3.26  | 1500 | 1.0997          | 0.3333   | 0.1667 |
| 1.1           | 4.35  | 2000 | 1.0989          | 0.3333   | 0.1667 |
| 1.0998        | 5.43  | 2500 | 1.0989          | 0.3333   | 0.1667 |
| 1.0995        | 6.52  | 3000 | 1.0987          | 0.3333   | 0.1667 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
