| | --- |
| | language: |
| | - pt |
| | license: apache-2.0 |
| | base_model: openai/whisper-tiny |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - PolyAI/minds14 |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: Whisper Tiny en - thiagoms |
| | results: |
| | - task: |
| | name: Automatic Speech Recognition |
| | type: automatic-speech-recognition |
| | dataset: |
| | name: Common Voice 13 |
| | type: PolyAI/minds14 |
| | config: en-US |
| | split: train |
| | args: en-US |
| | metrics: |
| | - name: Wer |
| | type: wer |
| | value: 0.3654073199527745 |
| | --- |
| | |
| | <!-- 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 en - thiagoms |
| |
|
| | This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 13 dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7762 |
| | - Wer Ortho: 0.3658 |
| | - Wer: 0.3654 |
| |
|
| | ## 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: 2000 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| |
| | | 0.0007 | 17.86 | 500 | 0.6431 | 0.3578 | 0.3548 | |
| | | 0.0002 | 35.71 | 1000 | 0.7066 | 0.3664 | 0.3648 | |
| | | 0.0001 | 53.57 | 1500 | 0.7466 | 0.3683 | 0.3672 | |
| | | 0.0001 | 71.43 | 2000 | 0.7762 | 0.3658 | 0.3654 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.31.0 |
| | - Pytorch 2.0.0+cu117 |
| | - Datasets 2.14.4 |
| | - Tokenizers 0.13.3 |
| | |
