metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: wolof-finetuned-ner
results: []
wolof-finetuned-ner
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4051
- Precision: 0.7944
- Recall: 0.8673
- F1: 0.8293
- Accuracy: 0.9852
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: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 226 | 0.4422 | 0.8253 | 0.8197 | 0.8225 | 0.9859 |
No log | 2.0 | 452 | 0.4051 | 0.7944 | 0.8673 | 0.8293 | 0.9852 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3