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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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- SLR35 |
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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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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: SLR Javanenese |
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type: SLR35 |
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args: 'config: java, split: train, test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 38.373095717160105 |
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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 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9356 |
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- Wer: 38.3731 |
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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: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 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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| 0.8832 | 0.1 | 100 | 0.9373 | 51.7965 | |
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| 0.3579 | 1.075 | 200 | 0.9986 | 51.4516 | |
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| 0.2348 | 2.05 | 300 | 0.9892 | 46.0765 | |
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| 0.1397 | 3.025 | 400 | 1.0404 | 47.0250 | |
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| 0.0836 | 3.125 | 500 | 0.9862 | 46.9531 | |
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| 0.0515 | 4.1 | 600 | 1.0148 | 42.2248 | |
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| 0.0222 | 5.075 | 700 | 0.9917 | 40.2846 | |
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| 0.0191 | 6.05 | 800 | 0.9665 | 39.3360 | |
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| 0.0078 | 7.025 | 900 | 0.9541 | 39.0486 | |
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| 0.0009 | 7.125 | 1000 | 0.9356 | 38.3731 | |
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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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