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---
language:
- he
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- ivrit-ai/whisper-training
metrics:
- wer
model-index:
- name: Whisper Tiny 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: 55.88158581116328
---
<!-- 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 Tiny Hebrew
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the ivrit-ai/whisper-training dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6254
- Wer: 55.8816
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.973 | 0.13 | 500 | 0.8480 | 77.6213 |
| 0.9024 | 0.25 | 1000 | 0.7710 | 67.9838 |
| 0.8049 | 0.38 | 1500 | 0.7499 | 66.7384 |
| 0.7221 | 0.5 | 2000 | 0.7092 | 64.7953 |
| 0.7464 | 0.63 | 2500 | 0.6939 | 62.7543 |
| 0.7396 | 0.75 | 3000 | 0.6839 | 62.5261 |
| 0.7336 | 0.88 | 3500 | 0.6716 | 61.2350 |
| 0.6118 | 1.01 | 4000 | 0.6512 | 58.4637 |
| 0.6299 | 1.13 | 4500 | 0.6564 | 60.1721 |
| 0.6318 | 1.26 | 5000 | 0.6475 | 58.8550 |
| 0.6315 | 1.38 | 5500 | 0.6361 | 58.9724 |
| 0.6081 | 1.51 | 6000 | 0.6321 | 57.1596 |
| 0.6487 | 1.63 | 6500 | 0.6459 | 58.5616 |
| 0.6481 | 1.76 | 7000 | 0.6298 | 56.9379 |
| 0.5833 | 1.88 | 7500 | 0.6303 | 57.8965 |
| 0.5689 | 2.01 | 8000 | 0.6305 | 56.1750 |
| 0.5223 | 2.14 | 8500 | 0.6335 | 56.6967 |
| 0.574 | 2.26 | 9000 | 0.6248 | 55.3730 |
| 0.5841 | 2.39 | 9500 | 0.6320 | 55.6273 |
| 0.5533 | 2.51 | 10000 | 0.6254 | 55.8816 |
### Framework versions
- Transformers 4.40.0.dev0
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2
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