metadata
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- >-
Custom_activation_from_scratch
train_whisper(12layerschange,10000_2000_2000_200)
- generated_from_trainer
datasets:
- darija-c
metrics:
- bleu
model-index:
- name: 'Whisper small darija translate '
results: []
Whisper small darija translate
This model is a fine-tuned version of openai/whisper-small on the Darija-C dataset. It achieves the following results on the evaluation set:
- Loss: 0.0001
- Bleu: 0.6434
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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: 2000
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 0.7235 | 133.3333 | 2000 | 0.5970 | 0.05 |
| 0.0257 | 266.6667 | 4000 | 0.0500 | 0.6200 |
| 0.0003 | 400.0 | 6000 | 0.0002 | 0.7200 |
| 0.0001 | 533.3333 | 8000 | 0.0001 | 0.6567 |
| 0.0001 | 666.6667 | 10000 | 0.0001 | 0.6434 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 2.19.2
- Tokenizers 0.20.3