transformers safetensors seamless_m4t_v2 feature-extraction generated_from_trainer ar dataset:darija-c base_model:facebook/seamless-m4t-medium base_model:finetune:facebook/seamless-m4t-medium license:cc-by-nc-4.0 endpoints_compatible region:us
---
base_model: facebook/seamless-m4t-medium
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-medium for darija speech translation
  results: []
---

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# Finetuned seamless-m4t-medium for darija speech translation

This model is a fine-tuned version of [facebook/seamless-m4t-medium](https://huggingface.co/facebook/seamless-m4t-medium) on the Darija-C dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9487
- Bleu: 0.6520

## 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   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 11.4385       | 12.5  | 50   | 7.7186          | 0.0    |
| 7.0056        | 25.0  | 100  | 4.6583          | 0.0    |
| 4.7721        | 37.5  | 150  | 3.4895          | 0.0402 |
| 3.9618        | 50.0  | 200  | 2.7834          | 0.0324 |
| 3.2307        | 62.5  | 250  | 2.3169          | 0.0601 |
| 2.9341        | 75.0  | 300  | 2.1102          | 0.0969 |
| 2.5517        | 87.5  | 350  | 1.9636          | 0.1041 |
| 2.3681        | 100.0 | 400  | 1.8770          | 0.0888 |
| 2.1031        | 112.5 | 450  | 1.7589          | 0.1302 |
| 2.1191        | 125.0 | 500  | 1.6578          | 0.1765 |
| 1.9185        | 137.5 | 550  | 1.5659          | 0.1802 |
| 1.9021        | 150.0 | 600  | 1.4514          | 0.4482 |
| 2.0155        | 162.5 | 650  | 1.3543          | 0.3924 |
| 1.8151        | 175.0 | 700  | 1.3195          | 0.3651 |
| 1.7461        | 187.5 | 750  | 1.1878          | 0.4723 |
| 1.6512        | 200.0 | 800  | 1.1107          | 0.5124 |
| 1.6378        | 212.5 | 850  | 1.0550          | 0.5922 |
| 1.4851        | 225.0 | 900  | 0.9948          | 0.6548 |
| 1.5016        | 237.5 | 950  | 0.9596          | 0.6390 |
| 1.4868        | 250.0 | 1000 | 0.9487          | 0.6520 |


### Framework versions

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