|
--- |
|
license: mit |
|
base_model: Davlan/afro-xlmr-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: angela_diacritics_shuffle_eval |
|
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. --> |
|
|
|
# angela_diacritics_shuffle_eval |
|
|
|
This model is a fine-tuned version of [Davlan/afro-xlmr-base](https://huggingface.co/Davlan/afro-xlmr-base) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3073 |
|
- Precision: 0.4269 |
|
- Recall: 0.1883 |
|
- F1: 0.2613 |
|
- Accuracy: 0.9206 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 5 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| 0.2305 | 1.0 | 1283 | 0.2759 | 0.3933 | 0.0827 | 0.1367 | 0.9186 | |
|
| 0.2064 | 2.0 | 2566 | 0.2674 | 0.4265 | 0.1068 | 0.1709 | 0.9197 | |
|
| 0.1856 | 3.0 | 3849 | 0.2924 | 0.4325 | 0.1405 | 0.2121 | 0.9201 | |
|
| 0.1688 | 4.0 | 5132 | 0.2899 | 0.4235 | 0.1802 | 0.2528 | 0.9201 | |
|
| 0.1449 | 5.0 | 6415 | 0.3073 | 0.4269 | 0.1883 | 0.2613 | 0.9206 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.31.0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.14.3 |
|
- Tokenizers 0.13.3 |
|
|
