---
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_delta
  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: 0.3333333333333333
    - name: F1
      type: f1
      value: 0.16666666666666666
---

<!-- 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_delta

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: 11213
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.0872        | 1.09  | 500  | 1.0884          | 0.3978   | 0.3194 |
| 1.0993        | 2.17  | 1000 | 1.0988          | 0.3333   | 0.1667 |
| 1.0983        | 3.26  | 1500 | 1.1525          | 0.3329   | 0.1713 |
| 1.0994        | 4.35  | 2000 | 1.0997          | 0.3333   | 0.1667 |
| 1.0998        | 5.43  | 2500 | 1.0991          | 0.3333   | 0.1667 |
| 1.0997        | 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