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--- |
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language: |
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- he |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- ivrit-ai/whisper-training |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Hebrew |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: ivrit-ai/whisper-training |
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type: ivrit-ai/whisper-training |
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args: 'config: he, split: train' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 37.8652 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper Small Hebrew |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ivrit-ai/whisper-training dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4241 |
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- Wer: 37.8652 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 10000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:| |
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| 0.4946 | 0.13 | 500 | 0.4572 | 46.4463 | |
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| 0.4629 | 0.25 | 1000 | 0.4492 | 43.7663 | |
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| 0.4067 | 0.38 | 1500 | 0.4337 | 42.6317 | |
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| 0.3663 | 0.5 | 2000 | 0.3892 | 41.8427 | |
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| 0.3857 | 0.63 | 2500 | 0.4017 | 40.7473 | |
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| 0.3795 | 0.75 | 3000 | 0.4011 | 39.4823 | |
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| 0.368 | 0.88 | 3500 | 0.3967 | 39.9778 | |
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| 0.2353 | 1.01 | 4000 | 0.3801 | 38.3281 | |
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| 0.2405 | 1.13 | 4500 | 0.4062 | 41.5428 | |
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| 0.2512 | 1.26 | 5000 | 0.3975 | 38.6215 | |
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| 0.2433 | 1.38 | 5500 | 0.4035 | 38.5824 | |
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| 0.2368 | 1.51 | 6000 | 0.3983 | 37.8652 | |
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| 0.2592 | 1.63 | 6500 | 0.4184 | 39.1041 | |
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| 0.2629 | 1.76 | 7000 | 0.4000 | 39.5475 | |
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| 0.2318 | 1.88 | 7500 | 0.4012 | 39.1954 | |
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| 0.1658 | 2.01 | 8000 | 0.3941 | 39.1367 | |
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| 0.1546 | 2.14 | 8500 | 0.4226 | 39.8865 | |
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| 0.1665 | 2.26 | 9000 | 0.4295 | 40.9755 | |
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| 0.1642 | 2.39 | 9500 | 0.4314 | 41.1255 | |
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| 0.1694 | 2.51 | 10000 | 0.4241 | 40.6755 | |
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### Framework versions |
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- Transformers 4.40.0.dev0 |
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- Pytorch 2.2.1 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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