metadata
library_name: transformers
language:
- ar
license: mit
base_model: facebook/s2t-medium-mustc-multilingual-st
tags:
- generated_from_trainer
datasets:
- darija-c
metrics:
- bleu
model-index:
- name: Finetuned-facebook-s2t-for-darija-speech-translation
results: []
Finetuned-facebook-s2t-for-darija-speech-translation
This model is a fine-tuned version of facebook/s2t-medium-mustc-multilingual-st on the Darija-C dataset. It achieves the following results on the evaluation set:
- Loss: 5.7855
- Bleu: 0.0032
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 9.1689 | 12.5 | 50 | 8.4431 | 0.0 |
| 7.9984 | 25.0 | 100 | 7.6555 | 0.0 |
| 7.4717 | 37.5 | 150 | 7.2774 | 0.0 |
| 7.2484 | 50.0 | 200 | 7.1061 | 0.0 |
| 7.0982 | 62.5 | 250 | 6.9703 | 0.0 |
| 6.9724 | 75.0 | 300 | 6.8526 | 0.0011 |
| 6.8564 | 87.5 | 350 | 6.7225 | 0.0034 |
| 6.7332 | 100.0 | 400 | 6.6144 | 0.0034 |
| 6.6511 | 112.5 | 450 | 6.5264 | 0.0034 |
| 6.5283 | 125.0 | 500 | 6.4174 | 0.0034 |
| 6.4477 | 137.5 | 550 | 6.3187 | 0.0034 |
| 6.3455 | 150.0 | 600 | 6.2208 | 0.0031 |
| 6.2683 | 162.5 | 650 | 6.0831 | 0.0034 |
| 6.1757 | 175.0 | 700 | 6.0449 | 0.0032 |
| 6.1017 | 187.5 | 750 | 5.9507 | 0.0034 |
| 6.0438 | 200.0 | 800 | 5.8899 | 0.0032 |
| 5.9752 | 212.5 | 850 | 5.8447 | 0.0034 |
| 5.9657 | 225.0 | 900 | 5.8105 | 0.0032 |
| 5.925 | 237.5 | 950 | 5.7858 | 0.0032 |
| 5.9142 | 250.0 | 1000 | 5.7855 | 0.0032 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 2.19.2
- Tokenizers 0.21.0