| | --- |
| | license: apache-2.0 |
| | tags: |
| | - whisper-event |
| | - generated_from_trainer |
| | datasets: |
| | - google/fleurs |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: Whisper Medium MS - Augmented |
| | results: |
| | - task: |
| | type: automatic-speech-recognition |
| | name: Automatic Speech Recognition |
| | dataset: |
| | name: google/fleurs |
| | type: google/fleurs |
| | config: ms_my |
| | split: test |
| | args: ms_my |
| | metrics: |
| | - type: wer |
| | value: 9.578362255965294 |
| | name: WER |
| | - type: cer |
| | value: 2.8109053797929726 |
| | name: CER |
| | --- |
| | |
| | <!-- 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 Medium MS - Augmented |
| |
|
| | This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the google/fleurs dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2066 |
| | - Wer: 9.5784 |
| | - Cer: 2.8109 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | Training: |
| | - [google/fleurs](https://huggingface.co/datasets/google/fleurs) (train+validation) |
| |
|
| | Evaluation: |
| | - [google/fleurs](https://huggingface.co/datasets/google/fleurs) (test) |
| |
|
| | ## Training procedure |
| |
|
| | Datasets were augmented on-the-fly using [audiomentations](https://github.com/iver56/audiomentations) via PitchShift and TimeStretch transformations at `p=0.3`. |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 1e-05 |
| | - train_batch_size: 2 |
| | - eval_batch_size: 2 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 16 |
| | - total_train_batch_size: 32 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 100 |
| | - training_steps: 1000 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:| |
| | | 0.0876 | 2.15 | 200 | 0.1949 | 10.3105 | 3.0685 | |
| | | 0.0064 | 4.3 | 400 | 0.1974 | 9.7004 | 2.9596 | |
| | | 0.0014 | 6.45 | 600 | 0.2031 | 9.6190 | 2.8955 | |
| | | 0.001 | 8.6 | 800 | 0.2058 | 9.6055 | 2.8440 | |
| | | 0.0009 | 10.75 | 1000 | 0.2066 | 9.5784 | 2.8109 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.26.0.dev0 |
| | - Pytorch 1.13.0+cu117 |
| | - Datasets 2.7.1.dev0 |
| | - Tokenizers 0.13.2 |
| |
|
