metadata
license: mit
base_model: Davlan/afro-xlmr-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: angela_punc_shuffle_eval
results: []
angela_punc_shuffle_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: 0.3164
- Precision: 0.4292
- Recall: 0.2191
- F1: 0.2901
- Accuracy: 0.9218
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 |
|---|---|---|---|---|---|---|---|
| 0.1532 | 1.0 | 1283 | 0.2538 | 0.4284 | 0.1218 | 0.1897 | 0.9213 |
| 0.1309 | 2.0 | 2566 | 0.2672 | 0.4457 | 0.1419 | 0.2152 | 0.9218 |
| 0.1136 | 3.0 | 3849 | 0.2666 | 0.4340 | 0.1806 | 0.2551 | 0.9215 |
| 0.0904 | 4.0 | 5132 | 0.2973 | 0.4555 | 0.1957 | 0.2738 | 0.9235 |
| 0.0751 | 5.0 | 6415 | 0.3164 | 0.4292 | 0.2191 | 0.2901 | 0.9218 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3