<!-- 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. -->
opus-mt-tc-big-en-ar-finetuned-franco-to-arabic-1
This model is a fine-tuned version of Helsinki-NLP/opus-mt-tc-big-en-ar on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.1589
- Bleu: 27.737
- Gen Len: 20.9565
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: 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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 1.0 | 13 | 3.2371 | 9.9987 | 21.0 |
| No log | 2.0 | 26 | 3.1023 | 10.8123 | 19.7826 |
| No log | 3.0 | 39 | 2.9474 | 9.0815 | 20.4783 |
| No log | 4.0 | 52 | 2.8274 | 11.6434 | 21.3478 |
| No log | 5.0 | 65 | 2.6879 | 11.6494 | 21.4348 |
| No log | 6.0 | 78 | 2.6243 | 16.1661 | 21.2174 |
| No log | 7.0 | 91 | 2.5342 | 16.5707 | 22.1304 |
| No log | 8.0 | 104 | 2.5489 | 17.885 | 20.2609 |
| No log | 9.0 | 117 | 2.4488 | 17.6415 | 20.4348 |
| No log | 10.0 | 130 | 2.4177 | 18.5943 | 20.5652 |
| No log | 11.0 | 143 | 2.3239 | 20.0857 | 21.3043 |
| No log | 12.0 | 156 | 2.2723 | 22.9544 | 21.4348 |
| No log | 13.0 | 169 | 2.2456 | 25.4455 | 21.5217 |
| No log | 14.0 | 182 | 2.2628 | 24.8757 | 21.2609 |
| No log | 15.0 | 195 | 2.2229 | 26.0051 | 21.3478 |
| No log | 16.0 | 208 | 2.2090 | 27.6742 | 20.8261 |
| No log | 17.0 | 221 | 2.1762 | 26.7048 | 21.3913 |
| No log | 18.0 | 234 | 2.1786 | 27.7328 | 21.1304 |
| No log | 19.0 | 247 | 2.1631 | 27.7187 | 21.2174 |
| No log | 20.0 | 260 | 2.1589 | 27.737 | 20.9565 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Tokenizers 0.13.3
