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--- |
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base_model: openai/whisper-large-v3 |
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datasets: |
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- clt013/malay-speech-3k-rows-dataset_v2 |
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language: |
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- ms |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Whisper Large v3 FT Malay - CLT013 |
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results: [] |
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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 Large v3 FT Malay - CLT013 |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Malay Speech 3k dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7194 |
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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: 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: 100 |
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- num_epochs: 3 |
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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 | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.5614 | 0.0933 | 25 | 2.6198 | |
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| 2.9109 | 0.1866 | 50 | 2.5967 | |
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| 2.5414 | 0.2799 | 75 | 2.5518 | |
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| 2.4919 | 0.3731 | 100 | 2.4742 | |
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| 2.5861 | 0.4664 | 125 | 2.3639 | |
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| 2.454 | 0.5597 | 150 | 2.2213 | |
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| 2.32 | 0.6530 | 175 | 2.0616 | |
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| 2.1081 | 0.7463 | 200 | 1.8668 | |
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| 1.7976 | 0.8396 | 225 | 1.6736 | |
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| 1.7597 | 0.9328 | 250 | 1.5280 | |
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| 1.469 | 1.0261 | 275 | 1.4172 | |
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| 1.4484 | 1.1194 | 300 | 1.3275 | |
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| 1.2641 | 1.2127 | 325 | 1.2592 | |
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| 1.1853 | 1.3060 | 350 | 1.1972 | |
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| 1.184 | 1.3993 | 375 | 1.1449 | |
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| 1.1733 | 1.4925 | 400 | 1.0964 | |
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| 1.0707 | 1.5858 | 425 | 1.0568 | |
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| 0.9975 | 1.6791 | 450 | 1.0172 | |
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| 0.9897 | 1.7724 | 475 | 0.9855 | |
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| 1.0223 | 1.8657 | 500 | 0.9524 | |
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| 0.875 | 1.9590 | 525 | 0.9232 | |
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| 0.9242 | 2.0522 | 550 | 0.8968 | |
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| 0.8829 | 2.1455 | 575 | 0.8709 | |
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| 0.8491 | 2.2388 | 600 | 0.8454 | |
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| 0.7793 | 2.3321 | 625 | 0.8236 | |
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| 0.7733 | 2.4254 | 650 | 0.7993 | |
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| 0.7085 | 2.5187 | 675 | 0.7787 | |
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| 0.7403 | 2.6119 | 700 | 0.7596 | |
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| 0.7019 | 2.7052 | 725 | 0.7415 | |
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| 0.722 | 2.7985 | 750 | 0.7309 | |
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| 0.6403 | 2.8918 | 775 | 0.7220 | |
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| 0.699 | 2.9851 | 800 | 0.7194 | |
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### Framework versions |
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- PEFT 0.13.0 |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
