metadata
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_beta
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
scenario-TCR-XLMV_data-cardiffnlp_tweet_sentiment_multilingual_all_beta
This model is a fine-tuned version of facebook/xlm-v-base on the tweet_sentiment_multilingual dataset. It achieves the following results on the evaluation set:
- Loss: 1.0990
- 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: 112233
- 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 |
|---|---|---|---|---|---|
| 1.1002 | 1.09 | 500 | 1.0988 | 0.3333 | 0.1667 |
| 1.0994 | 2.17 | 1000 | 1.0994 | 0.3333 | 0.1667 |
| 1.0989 | 3.26 | 1500 | 1.0996 | 0.3333 | 0.1667 |
| 1.1001 | 4.35 | 2000 | 1.0988 | 0.3333 | 0.1667 |
| 1.0997 | 5.43 | 2500 | 1.0987 | 0.3333 | 0.1667 |
| 1.0997 | 6.52 | 3000 | 1.0990 | 0.3333 | 0.1667 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3