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--- |
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license: apache-2.0 |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- audiofolder |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Medium Bambara Fieldwork |
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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: audiofolder |
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type: audiofolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Wer |
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type: wer |
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value: 157.60036917397323 |
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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 Medium Bambara Fieldwork |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.0725 |
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- Wer: 157.6004 |
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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: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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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: 500 |
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- training_steps: 13532 |
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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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| 0.6342 | 1.03 | 1000 | 2.5810 | 159.5293 | |
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| 0.2873 | 3.03 | 2000 | 2.9513 | 159.1140 | |
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| 0.1461 | 5.02 | 3000 | 3.6833 | 158.3941 | |
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| 0.049 | 7.02 | 4000 | 4.0725 | 157.6004 | |
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| 0.0218 | 9.01 | 5000 | 4.2531 | 158.3664 | |
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| 0.0071 | 11.0 | 6000 | 4.5944 | 157.9972 | |
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| 0.0057 | 12.04 | 7000 | 4.6659 | 161.4952 | |
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| 0.0061 | 14.03 | 8000 | 4.9162 | 161.0614 | |
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| 0.0042 | 16.03 | 9000 | 5.0205 | 158.9848 | |
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| 0.0007 | 18.02 | 10000 | 5.1463 | 159.1970 | |
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| 0.0015 | 20.01 | 11000 | 5.2150 | 159.0401 | |
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| 0.0001 | 22.01 | 12000 | 5.3008 | 159.5478 | |
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| 0.0001 | 24.0 | 13000 | 5.3800 | 159.0309 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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