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---
license: mit
base_model: vonewman/xlm-roberta-large-finetuned-wolof
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: wolof-finetuned-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wolof-finetuned-ner
This model is a fine-tuned version of [vonewman/xlm-roberta-large-finetuned-wolof](https://huggingface.co/vonewman/xlm-roberta-large-finetuned-wolof) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2264
- Precision: 0.7135
- Recall: 0.8639
- F1: 0.7815
- Accuracy: 0.9831
## 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: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 226 | 0.2264 | 0.7135 | 0.8639 | 0.7815 | 0.9831 |
### Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
|