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--- |
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language: |
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- En |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- speech_command_v0.02 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small speech command - Fati pd |
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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: Speech commands |
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type: speech_command_v0.02 |
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config: null |
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split: None |
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args: 'config: v0.02, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.3861003861003861 |
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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 speech command - Fati pd |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Speech commands dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0021 |
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- Wer: 0.3861 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 250 |
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- training_steps: 3000 |
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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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| 0.0095 | 0.2 | 250 | 0.0042 | 0.7239 | |
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| 0.0068 | 0.4 | 500 | 0.0051 | 1.0135 | |
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| 0.0045 | 0.6 | 750 | 0.0021 | 0.3861 | |
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| 0.0056 | 0.8 | 1000 | 0.0018 | 1.5927 | |
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| 0.0021 | 1.0 | 1250 | 0.0023 | 8.8803 | |
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| 0.0081 | 1.2 | 1500 | 0.0033 | 2.0270 | |
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| 0.0056 | 1.4 | 1750 | 0.0023 | 6.1293 | |
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| 0.0028 | 1.6 | 2000 | 0.0017 | 0.8687 | |
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| 0.0064 | 1.81 | 2250 | 0.0011 | 0.8687 | |
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| 0.0005 | 2.01 | 2500 | 0.0014 | 2.0270 | |
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| 0.0015 | 2.21 | 2750 | 0.0013 | 1.4961 | |
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| 0.0012 | 2.41 | 3000 | 0.0014 | 1.8822 | |
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### Framework versions |
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- Transformers 4.30.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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