metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- news_commentary
metrics:
- bleu
model-index:
- name: opus-mt-ar-en-finetuned-ar-to-en
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: news_commentary
type: news_commentary
args: ar-en
metrics:
- name: Bleu
type: bleu
value: 32.8872
opus-mt-ar-en-finetuned-ar-to-en
This model is a fine-tuned version of Helsinki-NLP/opus-mt-ar-en on the news_commentary dataset. It achieves the following results on the evaluation set:
- Loss: 0.6933
- Bleu: 32.8872
- Gen Len: 56.084
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 1.0 | 188 | 0.7407 | 30.7259 | 56.296 |
| No log | 2.0 | 376 | 0.6927 | 32.2038 | 58.602 |
| 0.8066 | 3.0 | 564 | 0.6898 | 33.1091 | 57.72 |
| 0.8066 | 4.0 | 752 | 0.6925 | 33.0842 | 56.574 |
| 0.8066 | 5.0 | 940 | 0.6933 | 32.8872 | 56.084 |
Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1