| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: ctrlv-speechrecognition-model |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # ctrlv-speechrecognition-model |
|
|
| This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the TIMIT dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4730 |
| - Wer: 0.3031 |
|
|
| ## Test WER in TIMIT dataset |
| - Wer: 0.189 |
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|
| [Google Colab Notebook](https://colab.research.google.com/drive/1M9ZbqvoRqshEccIlpTQGsgptpiGVgauH) |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 0.0001 |
| - train_batch_size: 32 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 1000 |
| - num_epochs: 60 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | 3.53 | 3.45 | 500 | 1.4021 | 0.9307 | |
| | 0.6077 | 6.9 | 1000 | 0.4255 | 0.4353 | |
| | 0.2331 | 10.34 | 1500 | 0.3887 | 0.3650 | |
| | 0.1436 | 13.79 | 2000 | 0.3579 | 0.3393 | |
| | 0.1021 | 17.24 | 2500 | 0.4447 | 0.3440 | |
| | 0.0797 | 20.69 | 3000 | 0.4041 | 0.3291 | |
| | 0.0657 | 24.14 | 3500 | 0.4262 | 0.3368 | |
| | 0.0525 | 27.59 | 4000 | 0.4937 | 0.3429 | |
| | 0.0454 | 31.03 | 4500 | 0.4449 | 0.3244 | |
| | 0.0373 | 34.48 | 5000 | 0.4363 | 0.3288 | |
| | 0.0321 | 37.93 | 5500 | 0.4519 | 0.3204 | |
| | 0.0288 | 41.38 | 6000 | 0.4440 | 0.3145 | |
| | 0.0259 | 44.83 | 6500 | 0.4691 | 0.3182 | |
| | 0.0203 | 48.28 | 7000 | 0.5062 | 0.3162 | |
| | 0.0171 | 51.72 | 7500 | 0.4762 | 0.3129 | |
| | 0.0166 | 55.17 | 8000 | 0.4772 | 0.3090 | |
| | 0.0147 | 58.62 | 8500 | 0.4730 | 0.3031 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.11.3 |
| - Pytorch 1.10.0+cu111 |
| - Datasets 1.18.3 |
| - Tokenizers 0.10.3 |
