| | --- |
| | license: apache-2.0 |
| | base_model: openai/whisper-tiny |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - PolyAI/minds14 |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: whisper-tiny-en-US |
| | results: |
| | - task: |
| | name: Automatic Speech Recognition |
| | type: automatic-speech-recognition |
| | dataset: |
| | name: PolyAI/minds14 |
| | type: PolyAI/minds14 |
| | config: en-US |
| | split: train[450:] |
| | args: en-US |
| | metrics: |
| | - name: Wer |
| | type: wer |
| | value: 0.3435655253837072 |
| | --- |
| | |
| | <!-- 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-US |
| |
|
| | This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.6286 |
| | - Wer Ortho: 0.3430 |
| | - Wer: 0.3436 |
| |
|
| | ## 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: 5e-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: constant_with_warmup |
| | - lr_scheduler_warmup_steps: 10 |
| | - training_steps: 225 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| |
| | | 3.2798 | 0.25 | 14 | 0.9783 | 0.7218 | 0.6889 | |
| | | 0.6283 | 0.5 | 28 | 0.5667 | 0.4479 | 0.4427 | |
| | | 0.5574 | 0.75 | 42 | 0.5307 | 0.4812 | 0.4858 | |
| | | 0.501 | 1.0 | 56 | 0.5130 | 0.3800 | 0.3813 | |
| | | 0.2296 | 1.25 | 70 | 0.5057 | 0.3479 | 0.3436 | |
| | | 0.2296 | 1.5 | 84 | 0.5515 | 0.3572 | 0.3512 | |
| | | 0.2207 | 1.75 | 98 | 0.5356 | 0.3578 | 0.3530 | |
| | | 0.1928 | 2.0 | 112 | 0.5288 | 0.3226 | 0.3200 | |
| | | 0.0795 | 2.25 | 126 | 0.5532 | 0.3257 | 0.3259 | |
| | | 0.0651 | 2.5 | 140 | 0.5833 | 0.3504 | 0.3512 | |
| | | 0.0719 | 2.75 | 154 | 0.5931 | 0.3467 | 0.3501 | |
| | | 0.0722 | 3.0 | 168 | 0.5994 | 0.3498 | 0.3477 | |
| | | 0.0231 | 3.25 | 182 | 0.6030 | 0.3270 | 0.3264 | |
| | | 0.0433 | 3.5 | 196 | 0.6059 | 0.3214 | 0.3200 | |
| | | 0.0663 | 3.75 | 210 | 0.6262 | 0.3646 | 0.3648 | |
| | | 0.0396 | 4.0 | 224 | 0.6286 | 0.3430 | 0.3436 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.31.0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.3 |
| | - Tokenizers 0.13.3 |
| | |
