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--- |
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library_name: transformers |
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language: |
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- th |
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license: apache-2.0 |
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base_model: biodatlab/whisper-th-small-combined |
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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 Small Th Combined Finetuned |
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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: th |
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split: test |
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args: 'config: th, split: validated' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.41320489664860527 |
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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 Th Combined Finetuned |
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This model is a fine-tuned version of [biodatlab/whisper-th-small-combined](https://huggingface.co/biodatlab/whisper-th-small-combined) 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: 0.0702 |
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- Wer: 0.4132 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 4 |
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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: 1000 |
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- training_steps: 8000 |
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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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| 0.3362 | 0.2175 | 1000 | 0.1439 | 0.6061 | |
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| 0.2993 | 0.4349 | 2000 | 0.1230 | 0.5645 | |
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| 0.2523 | 0.6524 | 3000 | 0.1080 | 0.5299 | |
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| 0.2823 | 0.8698 | 4000 | 0.0939 | 0.4914 | |
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| 0.2459 | 1.0873 | 5000 | 0.0840 | 0.4570 | |
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| 0.2005 | 1.3047 | 6000 | 0.0776 | 0.4364 | |
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| 0.2081 | 1.5222 | 7000 | 0.0724 | 0.4157 | |
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| 0.1918 | 1.7396 | 8000 | 0.0702 | 0.4132 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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