| --- |
| language: |
| - sr |
| license: apache-2.0 |
| base_model: openai/whisper-small |
| tags: |
| - generated_from_trainer |
| datasets: |
| - google/fleurs |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Small Sr Fleurs- Sagicc |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Google Fleurs |
| type: google/fleurs |
| config: sr_rs |
| split: test |
| args: sr_rs |
| metrics: |
| - name: Wer |
| type: wer |
| value: 25.6021212344406 |
| --- |
| |
| <!-- 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 Small Sr Fleurs- Sagicc |
|
|
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Google Fleurs dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4134 |
| - Wer Ortho: 28.9292 |
| - Wer: 25.6021 |
|
|
| ## 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: 1e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: constant_with_warmup |
| - lr_scheduler_warmup_steps: 50 |
| - training_steps: 1000 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:| |
| | 0.0649 | 2.49 | 500 | 0.3685 | 30.6352 | 27.1489 | |
| | 0.0181 | 4.98 | 1000 | 0.4134 | 28.9292 | 25.6021 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.33.1 |
| - Pytorch 2.0.1+cu117 |
| - Datasets 2.14.5 |
| - Tokenizers 0.13.3 |
| |
