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README.md
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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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