metadata
license: mit
base_model: vonewman/xlm-roberta-base-finetuned-wolof
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: wolof-finetuned-ner
results: []
wolof-finetuned-ner
This model is a fine-tuned version of vonewman/xlm-roberta-base-finetuned-wolof on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3539
- Precision: 0.7798
- Recall: 0.8912
- F1: 0.8317
- Accuracy: 0.9850
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: 2e-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 | 0.3879 | 0.7412 | 0.8571 | 0.7950 | 0.9834 |
| No log | 2.0 | 452 | 0.3595 | 0.7378 | 0.8707 | 0.7988 | 0.9833 |
| 0.5119 | 3.0 | 678 | 0.3539 | 0.7798 | 0.8912 | 0.8317 | 0.9850 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3