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--- |
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library_name: transformers |
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language: |
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- jav |
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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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- generated_from_trainer |
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datasets: |
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- SLR41_35 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Java |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: SLR Javanenese 41_35 |
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type: SLR41_35 |
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args: 'config: java, split: train, test' |
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metrics: |
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- type: wer |
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value: 29.24663420223432 |
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name: Wer |
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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 Java |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the SLR Javanenese 41_35 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4200 |
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- Wer: 29.2466 |
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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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 1000 |
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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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| 0.4922 | 0.16 | 100 | 0.6047 | 37.4678 | |
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| 0.435 | 0.32 | 200 | 0.5572 | 35.9424 | |
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| 0.5688 | 0.48 | 300 | 0.5090 | 33.5649 | |
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| 0.4779 | 0.64 | 400 | 0.4799 | 31.8390 | |
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| 0.4247 | 0.8 | 500 | 0.4540 | 30.8364 | |
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| 0.42 | 0.96 | 600 | 0.4368 | 30.2492 | |
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| 0.2276 | 1.12 | 700 | 0.4330 | 29.6333 | |
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| 0.2137 | 1.28 | 800 | 0.4264 | 29.5832 | |
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| 0.236 | 1.44 | 900 | 0.4215 | 29.2395 | |
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| 0.1971 | 1.6 | 1000 | 0.4200 | 29.2466 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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