| | --- |
| | language: |
| | - de |
| | license: apache-2.0 |
| | base_model: openai/whisper-tiny |
| | tags: |
| | - hf-asr-leaderboard |
| | - generated_from_trainer |
| | datasets: |
| | - mozilla-foundation/common_voice_16_0 |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: Whisper Tiny CV de |
| | results: |
| | - task: |
| | name: Automatic Speech Recognition |
| | type: automatic-speech-recognition |
| | dataset: |
| | name: Common Voice 11.0 de 5% |
| | type: mozilla-foundation/common_voice_16_0 |
| | config: de |
| | split: None |
| | args: 'config: de, split: test' |
| | metrics: |
| | - name: Wer |
| | type: wer |
| | value: 72.91819291819291 |
| | --- |
| | |
| | <!-- 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 CV de |
| |
|
| | This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 de 5% dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7117 |
| | - Wer: 72.9182 |
| |
|
| | ## 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: 1.35e-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: 250 |
| | - training_steps: 2000 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:------:|:----:|:---------------:|:-------:| |
| | | 0.6076 | 0.2252 | 250 | 0.8347 | 76.3126 | |
| | | 0.5955 | 0.4505 | 500 | 0.7893 | 79.1697 | |
| | | 0.5179 | 0.6757 | 750 | 0.7593 | 82.1978 | |
| | | 0.5189 | 0.9009 | 1000 | 0.7370 | 73.0159 | |
| | | 0.3644 | 1.1261 | 1250 | 0.7254 | 84.1270 | |
| | | 0.394 | 1.3514 | 1500 | 0.7183 | 73.4066 | |
| | | 0.3672 | 1.5766 | 1750 | 0.7152 | 73.1136 | |
| | | 0.3751 | 1.8018 | 2000 | 0.7117 | 72.9182 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.41.2 |
| | - Pytorch 2.3.0+cu121 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| | |
