metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-base-wolof
results: []
xlm-roberta-base-wolof
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2733
- Precision: 0.7251
- Recall: 0.7220
- F1: 0.7236
- Accuracy: 0.9586
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: 4.899923663123727e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 226 | 0.2416 | 0.7653 | 0.6519 | 0.7041 | 0.9587 |
| No log | 2.0 | 452 | 0.2573 | 0.6917 | 0.7300 | 0.7104 | 0.9568 |
| 0.0212 | 3.0 | 678 | 0.2733 | 0.7251 | 0.7220 | 0.7236 | 0.9586 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3