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: 0.2937
- Precision: 0.8082
- Recall: 0.8741
- F1: 0.8399
- Accuracy: 0.9871
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 | 0.2625 | 0.7522 | 0.8571 | 0.8013 | 0.9846 |
No log | 2.0 | 452 | 0.3009 | 0.7857 | 0.8605 | 0.8214 | 0.9854 |
0.365 | 3.0 | 678 | 0.2937 | 0.8082 | 0.8741 | 0.8399 | 0.9871 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3