transformers safetensors whisper automatic-speech-recognition generated_from_trainer ar dataset:darija-c base_model:openai/whisper-large base_model:finetune:openai/whisper-large license:apache-2.0 endpoints_compatible region:us
---
base_model: openai/whisper-large
datasets:
- darija-c
language:
- ar
library_name: transformers
license: apache-2.0
metrics:
- bleu
tags:
- generated_from_trainer
model-index:
- name: Finetuned Whisper large for darija speech translation
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Finetuned Whisper large for darija speech translation

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the Darija-C dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Bleu: 0.7440

## 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: 1
- eval_batch_size: 1
- 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   |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 3.145         | 0.8333  | 50   | 1.7143          | 0.0074 |
| 1.5712        | 1.6667  | 100  | 0.9313          | 0.0557 |
| 0.8924        | 2.5     | 150  | 0.3534          | 0.4306 |
| 0.3915        | 3.3333  | 200  | 0.2014          | 0.5725 |
| 0.2762        | 4.1667  | 250  | 0.0874          | 0.5841 |
| 0.1136        | 5.0     | 300  | 0.0630          | 0.6672 |
| 0.0777        | 5.8333  | 350  | 0.0868          | 0.6594 |
| 0.0749        | 6.6667  | 400  | 0.0405          | 0.7117 |
| 0.0412        | 7.5     | 450  | 0.0217          | 0.7319 |
| 0.0046        | 8.3333  | 500  | 0.0414          | 0.7320 |
| 0.0516        | 9.1667  | 550  | 0.0007          | 0.7440 |
| 0.006         | 10.0    | 600  | 0.0001          | 0.7440 |
| 0.0001        | 10.8333 | 650  | 0.0005          | 0.7440 |
| 0.0006        | 11.6667 | 700  | 0.0000          | 0.7440 |
| 0.0           | 12.5    | 750  | 0.0000          | 0.7440 |
| 0.0           | 13.3333 | 800  | 0.0000          | 0.7440 |
| 0.0           | 14.1667 | 850  | 0.0000          | 0.7440 |
| 0.0           | 15.0    | 900  | 0.0000          | 0.7440 |
| 0.0           | 15.8333 | 950  | 0.0000          | 0.7440 |
| 0.0           | 16.6667 | 1000 | 0.0000          | 0.7440 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 2.19.2
- Tokenizers 0.21.0
