metadata
base_model: daveni/twitter-xlm-roberta-emotion-es
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: base
results: []
pipeline_tag: text-classification
base
This model is a fine-tuned version of daveni/twitter-xlm-roberta-emotion-es on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4881
- Accuracy: 0.8504
- F1: 0.8119
- Precision: 0.8454
- Recall: 0.7810
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.667 | 1.0 | 32 | 0.5528 | 0.7283 | 0.6057 | 0.7571 | 0.5048 |
| 0.5241 | 2.0 | 64 | 0.4843 | 0.7874 | 0.7065 | 0.8228 | 0.6190 |
| 0.3046 | 3.0 | 96 | 0.4785 | 0.8031 | 0.7423 | 0.8090 | 0.6857 |
| 0.1631 | 4.0 | 128 | 0.4776 | 0.8228 | 0.7644 | 0.8488 | 0.6952 |
| 0.097 | 5.0 | 160 | 0.4881 | 0.8504 | 0.8119 | 0.8454 | 0.7810 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.4.0
- Datasets 2.20.0
- Tokenizers 0.19.1