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--- |
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language: |
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- tr |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Medium Tr - Can K V2 |
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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: Common Voice 17.0 |
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type: mozilla-foundation/common_voice_17_0 |
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config: tr |
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split: test |
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args: 'config: tr, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 15.4185472196202 |
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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 Medium Tr - Can K V2 |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 17.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2285 |
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- Wer: 15.4185 |
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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: 8 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 12000 |
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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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| 0.203 | 0.3448 | 1000 | 0.2255 | 19.4192 | |
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| 0.1602 | 0.6895 | 2000 | 0.2142 | 18.0448 | |
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| 0.0814 | 1.0343 | 3000 | 0.2087 | 17.5338 | |
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| 0.0761 | 1.3791 | 4000 | 0.2060 | 17.1558 | |
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| 0.0734 | 1.7238 | 5000 | 0.1998 | 16.5052 | |
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| 0.0335 | 2.0686 | 6000 | 0.2073 | 16.7283 | |
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| 0.0344 | 2.4134 | 7000 | 0.2066 | 15.9091 | |
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| 0.0338 | 2.7581 | 8000 | 0.2023 | 15.3709 | |
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| 0.0099 | 3.1029 | 9000 | 0.2211 | 15.6331 | |
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| 0.0097 | 3.4477 | 10000 | 0.2254 | 15.6008 | |
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| 0.0096 | 3.7924 | 11000 | 0.2254 | 15.3334 | |
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| 0.0022 | 4.1372 | 12000 | 0.2285 | 15.4185 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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