| | --- |
| | language: |
| | - en |
| | license: apache-2.0 |
| | base_model: openai/whisper-tiny |
| | tags: |
| | - nyansapo_ai-asr-leaderboard |
| | - generated_from_trainer |
| | datasets: |
| | - NyansapoAI/azure-dataset |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: whisper-base.en |
| | results: |
| | - task: |
| | name: Automatic Speech Recognition |
| | type: automatic-speech-recognition |
| | dataset: |
| | name: Azure-dataset |
| | type: NyansapoAI/azure-dataset |
| | config: default |
| | split: test |
| | args: 'split: test' |
| | metrics: |
| | - name: Wer |
| | type: wer |
| | value: 8.585858585858585 |
| | --- |
| | |
| | <!-- 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-base.en |
| |
|
| | This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Azure-dataset dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0237 |
| | - Wer: 8.5859 |
| |
|
| | ## 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: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 500 |
| | - training_steps: 2500 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:| |
| | | 0.1945 | 3.11 | 500 | 0.0626 | 18.0808 | |
| | | 0.0627 | 6.21 | 1000 | 0.0292 | 10.5051 | |
| | | 0.0419 | 9.32 | 1500 | 0.0242 | 9.0909 | |
| | | 0.0419 | 12.42 | 2000 | 0.0242 | 8.8889 | |
| | | 0.0502 | 15.53 | 2500 | 0.0237 | 8.5859 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.33.0.dev0 |
| | - Pytorch 2.0.1 |
| | - Datasets 2.14.4 |
| | - Tokenizers 0.13.3 |
| | |
