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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: 54.11225658648339
---
<!-- 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: 0.8474
- Wer Ortho: 56.1657
- Wer: 54.1123
## 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: 500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.7394 | 1.76 | 500 | 0.8474 | 56.1657 | 54.1123 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
|