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--- |
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library_name: transformers |
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language: |
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- hi |
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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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- mozilla-foundation/common_voice_11_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Ori vi |
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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 11.0 |
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type: mozilla-foundation/common_voice_11_0 |
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args: 'config: hi, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 17.65774934574004 |
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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 Ori vi |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3950 |
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- Wer: 17.6577 |
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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 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: 200 |
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- training_steps: 1300 |
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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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| 1.1125 | 0.0667 | 30 | 0.9877 | 30.4667 | |
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| 0.9337 | 0.1333 | 60 | 0.7582 | 18.3338 | |
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| 0.7185 | 0.2 | 90 | 0.4716 | 16.3129 | |
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| 0.493 | 0.2667 | 120 | 0.4382 | 16.1893 | |
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| 0.4328 | 0.3333 | 150 | 0.4298 | 15.6223 | |
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| 0.4127 | 0.4 | 180 | 0.4208 | 16.8726 | |
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| 0.3865 | 0.4667 | 210 | 0.4171 | 20.0422 | |
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| 0.419 | 0.5333 | 240 | 0.4141 | 17.0835 | |
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| 0.4141 | 0.6 | 270 | 0.4157 | 15.8258 | |
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| 0.464 | 0.6667 | 300 | 0.4077 | 16.9235 | |
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| 0.4303 | 0.7333 | 330 | 0.4043 | 18.4865 | |
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| 0.4418 | 0.8 | 360 | 0.4050 | 16.7999 | |
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| 0.4786 | 0.8667 | 390 | 0.3981 | 15.1352 | |
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| 0.4238 | 0.9333 | 420 | 0.3953 | 17.0907 | |
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| 0.3986 | 1.0 | 450 | 0.3926 | 16.7054 | |
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| 0.2304 | 1.0667 | 480 | 0.3948 | 16.3928 | |
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| 0.2583 | 1.1333 | 510 | 0.3943 | 16.6327 | |
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| 0.2385 | 1.2 | 540 | 0.3997 | 15.1425 | |
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| 0.2126 | 1.2667 | 570 | 0.3985 | 15.0552 | |
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| 0.2259 | 1.3333 | 600 | 0.3970 | 16.5964 | |
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| 0.2237 | 1.4 | 630 | 0.3964 | 16.5382 | |
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| 0.2344 | 1.4667 | 660 | 0.3983 | 17.9485 | |
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| 0.2068 | 1.5333 | 690 | 0.3974 | 17.9703 | |
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| 0.2535 | 1.6 | 720 | 0.3950 | 17.6577 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.4.0 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.0 |
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