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---
language:
- he
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- ivrit-ai/whisper-training
metrics:
- wer
model-index:
- name: Whisper Small Hebrew
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: ivrit-ai/whisper-training
type: ivrit-ai/whisper-training
args: 'config: he, split: train'
metrics:
- name: Wer
type: wer
value: 37.8652
---
<!-- 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. -->
# Whisper Small Hebrew
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ivrit-ai/whisper-training dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4241
- Wer: 37.8652
## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.4946 | 0.13 | 500 | 0.4572 | 46.4463 |
| 0.4629 | 0.25 | 1000 | 0.4492 | 43.7663 |
| 0.4067 | 0.38 | 1500 | 0.4337 | 42.6317 |
| 0.3663 | 0.5 | 2000 | 0.3892 | 41.8427 |
| 0.3857 | 0.63 | 2500 | 0.4017 | 40.7473 |
| 0.3795 | 0.75 | 3000 | 0.4011 | 39.4823 |
| 0.368 | 0.88 | 3500 | 0.3967 | 39.9778 |
| 0.2353 | 1.01 | 4000 | 0.3801 | 38.3281 |
| 0.2405 | 1.13 | 4500 | 0.4062 | 41.5428 |
| 0.2512 | 1.26 | 5000 | 0.3975 | 38.6215 |
| 0.2433 | 1.38 | 5500 | 0.4035 | 38.5824 |
| 0.2368 | 1.51 | 6000 | 0.3983 | 37.8652 |
| 0.2592 | 1.63 | 6500 | 0.4184 | 39.1041 |
| 0.2629 | 1.76 | 7000 | 0.4000 | 39.5475 |
| 0.2318 | 1.88 | 7500 | 0.4012 | 39.1954 |
| 0.1658 | 2.01 | 8000 | 0.3941 | 39.1367 |
| 0.1546 | 2.14 | 8500 | 0.4226 | 39.8865 |
| 0.1665 | 2.26 | 9000 | 0.4295 | 40.9755 |
| 0.1642 | 2.39 | 9500 | 0.4314 | 41.1255 |
| 0.1694 | 2.51 | 10000 | 0.4241 | 40.6755 |
### Framework versions
- Transformers 4.40.0.dev0
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2
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