---
license: mit
base_model: facebook/xlm-v-base
tags:
- generated_from_trainer
datasets:
- tweet_sentiment_multilingual
metrics:
- accuracy
- f1
model-index:
- name: scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_alpha
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: tweet_sentiment_multilingual
      type: tweet_sentiment_multilingual
      config: all
      split: validation
      args: all
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6203703703703703
    - name: F1
      type: f1
      value: 0.620923254123051
---

<!-- 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. -->

# scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_alpha

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: 1.6081
- Accuracy: 0.6204
- F1: 0.6209

## 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: 1123
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.0299        | 1.09  | 500  | 0.8919          | 0.5992   | 0.5922 |
| 0.8433        | 2.17  | 1000 | 0.8574          | 0.6150   | 0.6101 |
| 0.7031        | 3.26  | 1500 | 0.9338          | 0.6354   | 0.6292 |
| 0.5854        | 4.35  | 2000 | 1.1318          | 0.6227   | 0.6207 |
| 0.4556        | 5.43  | 2500 | 1.1376          | 0.6277   | 0.6270 |
| 0.357         | 6.52  | 3000 | 1.1730          | 0.6208   | 0.6195 |
| 0.2777        | 7.61  | 3500 | 1.3259          | 0.6246   | 0.6211 |
| 0.2198        | 8.7   | 4000 | 1.6081          | 0.6204   | 0.6209 |


### Framework versions

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