| | --- |
| | license: apache-2.0 |
| | tags: |
| | - whisper-event |
| | - generated_from_trainer |
| | datasets: |
| | - NbAiLab/NCC_S3 |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: Whisper Tiny GPU test |
| | results: |
| | - task: |
| | name: Automatic Speech Recognition |
| | type: automatic-speech-recognition |
| | dataset: |
| | name: NbAiLab/NCC_S3 |
| | type: NbAiLab/NCC_S3 |
| | config: 'no' |
| | split: validation |
| | args: 'no' |
| | metrics: |
| | - name: Wer |
| | type: wer |
| | value: 51.37028014616322 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # Whisper Tiny GPU test |
| |
|
| | This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the NbAiLab/NCC_S3 dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.9375 |
| | - Wer: 51.3703 |
| | |
| | ## 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: 3e-06 |
| | - train_batch_size: 128 |
| | - eval_batch_size: 32 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: constant_with_warmup |
| | - lr_scheduler_warmup_steps: 200 |
| | - training_steps: 2000 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:| |
| | | 2.4574 | 0.1 | 200 | 1.4663 | 71.6504 | |
| | | 1.9587 | 0.2 | 400 | 1.2581 | 64.7381 | |
| | | 1.816 | 0.3 | 600 | 1.1672 | 60.9318 | |
| | | 1.7199 | 0.4 | 800 | 1.1006 | 57.6736 | |
| | | 1.6686 | 0.5 | 1000 | 1.0630 | 56.1815 | |
| | | 1.621 | 0.6 | 1200 | 1.0273 | 55.4811 | |
| | | 1.5846 | 0.7 | 1400 | 1.0017 | 53.9890 | |
| | | 1.5482 | 0.8 | 1600 | 0.9773 | 53.0146 | |
| | | 1.521 | 0.9 | 1800 | 0.9575 | 52.1011 | |
| | | 1.4932 | 1.0 | 2000 | 0.9375 | 51.3703 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.28.0.dev0 |
| | - Pytorch 1.13.0+cu117 |
| | - Datasets 2.7.1.dev0 |
| | - Tokenizers 0.13.2 |
| |
|
