metadata
license: mit
base_model: Davlan/afro-xlmr-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: angela_shuffle_punc_eval
results: []
angela_shuffle_punc_eval
This model is a fine-tuned version of Davlan/afro-xlmr-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2116
- Precision: 0.3859
- Recall: 0.3254
- F1: 0.3531
- Accuracy: 0.9334
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 |
|---|---|---|---|---|---|---|---|
| 0.1711 | 1.0 | 1283 | 0.1840 | 0.3850 | 0.1896 | 0.2540 | 0.9369 |
| 0.1439 | 2.0 | 2566 | 0.1923 | 0.3887 | 0.2629 | 0.3137 | 0.9331 |
| 0.1248 | 3.0 | 3849 | 0.2008 | 0.4106 | 0.2615 | 0.3195 | 0.9373 |
| 0.1076 | 4.0 | 5132 | 0.2012 | 0.3800 | 0.3472 | 0.3628 | 0.9318 |
| 0.089 | 5.0 | 6415 | 0.2116 | 0.3859 | 0.3254 | 0.3531 | 0.9334 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3