transformers safetensors seamless_m4t_v2 feature-extraction generated_from_trainer ar dataset:darija-c base_model:facebook/seamless-m4t-large base_model:finetune:facebook/seamless-m4t-large license:cc-by-nc-4.0 endpoints_compatible region:us
---
base_model: facebook/seamless-m4t-large
datasets:
- darija-c
language:
- ar
library_name: transformers
license: cc-by-nc-4.0
metrics:
- bleu
tags:
- generated_from_trainer
model-index:
- name: Finetuned seamless-m4t-large for darija speech translation
  results: []
---

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# Finetuned seamless-m4t-large for darija speech translation

This model is a fine-tuned version of [facebook/seamless-m4t-large](https://huggingface.co/facebook/seamless-m4t-large) on the Darija-C dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5449
- Bleu: 0.1562

## 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: 4
- 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   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 10.1923       | 12.5  | 50   | 7.8012          | 0.0    |
| 7.0388        | 25.0  | 100  | 4.9095          | 0.0023 |
| 4.1866        | 37.5  | 150  | 3.0521          | 0.0276 |
| 3.1409        | 50.0  | 200  | 2.4410          | 0.0653 |
| 2.581         | 62.5  | 250  | 2.1347          | 0.0795 |
| 2.2369        | 75.0  | 300  | 2.0097          | 0.0765 |
| 2.171         | 87.5  | 350  | 1.9385          | 0.0637 |
| 2.0371        | 100.0 | 400  | 1.8743          | 0.0907 |
| 1.9672        | 112.5 | 450  | 1.8273          | 0.0943 |
| 1.9463        | 125.0 | 500  | 1.7789          | 0.1028 |
| 1.8821        | 137.5 | 550  | 1.7346          | 0.1137 |
| 1.8424        | 150.0 | 600  | 1.7088          | 0.1208 |
| 1.836         | 162.5 | 650  | 1.6618          | 0.1470 |
| 1.757         | 175.0 | 700  | 1.6311          | 0.1347 |
| 1.7532        | 187.5 | 750  | 1.6137          | 0.1561 |
| 1.8539        | 200.0 | 800  | 1.5977          | 0.1184 |
| 1.7176        | 212.5 | 850  | 1.5758          | 0.1205 |
| 1.6944        | 225.0 | 900  | 1.5604          | 0.1396 |
| 1.7136        | 237.5 | 950  | 1.5521          | 0.1562 |
| 1.7354        | 250.0 | 1000 | 1.5449          | 0.1562 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
