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---
language:
- ar
license: mit
base_model: distil-whisper/distil-large-v2
tags:
- generated_from_trainer
datasets:
- nadsoft/Jordan-Audio
metrics:
- wer
model-index:
- name: Hamsa distill alfa
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: nadsoft/Jordan-Audio
type: nadsoft/Jordan-Audio
metrics:
- name: Wer
type: wer
value: 45.223367697594504
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Hamsa distill alfa
This model is a fine-tuned version of [distil-whisper/distil-large-v2](https://huggingface.co/distil-whisper/distil-large-v2) on the nadsoft/Jordan-Audio dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9732
- Wer Ortho: 47.5105
- Wer: 45.2234
## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 8000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.2094 | 7.04 | 2000 | 0.8198 | 48.5575 | 46.3918 |
| 0.0883 | 14.08 | 4000 | 0.9112 | 47.4174 | 44.6048 |
| 0.0662 | 21.13 | 6000 | 0.9644 | 46.8125 | 44.6277 |
| 0.0496 | 28.17 | 8000 | 0.9732 | 47.5105 | 45.2234 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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