|
--- |
|
license: apache-2.0 |
|
base_model: Helsinki-NLP/opus-mt-ar-en |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- bleu |
|
model-index: |
|
- name: darija-latin-to-english-new |
|
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. --> |
|
|
|
# darija-latin-to-english-new |
|
|
|
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ar-en](https://huggingface.co/Helsinki-NLP/opus-mt-ar-en) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0525 |
|
- Bleu: 29.8636 |
|
- Gen Len: 8.8467 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 5 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:| |
|
| No log | 0.36 | 100 | 0.0530 | 29.1142 | 8.8582 | |
|
| No log | 0.71 | 200 | 0.0530 | 28.9361 | 9.0068 | |
|
| No log | 1.07 | 300 | 0.0528 | 29.0076 | 8.6585 | |
|
| No log | 1.43 | 400 | 0.0531 | 29.1383 | 8.9458 | |
|
| 0.0229 | 1.79 | 500 | 0.0529 | 29.7316 | 8.6507 | |
|
| 0.0229 | 2.14 | 600 | 0.0529 | 30.0367 | 8.8326 | |
|
| 0.0229 | 2.5 | 700 | 0.0529 | 29.8774 | 8.8947 | |
|
| 0.0229 | 2.86 | 800 | 0.0526 | 29.4939 | 8.5792 | |
|
| 0.0229 | 3.21 | 900 | 0.0525 | 29.6445 | 8.877 | |
|
| 0.0219 | 3.57 | 1000 | 0.0525 | 29.5756 | 8.8233 | |
|
| 0.0219 | 3.93 | 1100 | 0.0525 | 29.7202 | 8.9447 | |
|
| 0.0219 | 4.29 | 1200 | 0.0526 | 29.6961 | 8.8869 | |
|
| 0.0219 | 4.64 | 1300 | 0.0526 | 29.9186 | 8.854 | |
|
| 0.0219 | 5.0 | 1400 | 0.0525 | 29.8636 | 8.8467 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.1 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.15.2 |
|
|