metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: AmharicNewsCharacterNormalized
results: []
AmharicNewsCharacterNormalized
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2054
- Accuracy: 0.9538
- Precision: 0.9539
- Recall: 0.9538
- F1: 0.9538
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.2737 | 1.0 | 945 | 0.1984 | 0.9175 | 0.9197 | 0.9175 | 0.9172 |
| 0.2651 | 2.0 | 1890 | 0.2313 | 0.9409 | 0.9408 | 0.9409 | 0.9407 |
| 0.2155 | 3.0 | 2835 | 0.1687 | 0.9480 | 0.9480 | 0.9480 | 0.9479 |
| 0.4065 | 4.0 | 3780 | 0.2072 | 0.9439 | 0.9483 | 0.9439 | 0.9443 |
| 0.0785 | 5.0 | 4725 | 0.2054 | 0.9538 | 0.9539 | 0.9538 | 0.9538 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1