Whisper Small ID - Common Voice 17
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.2892
- eval_wer: 17.9219
- eval_runtime: 1041.4909
- eval_samples_per_second: 3.496
- eval_steps_per_second: 0.438
- epoch: 3.8462
- step: 2000
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: 4000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
Training Environment
This model was trained on a single A100 GPU machine in Google Cloud. Below are the machine specifications:
| Machine Type | GPU Count | GPU Memory (GB HBM2) | vCPU Count | VM Memory (GB) | Local SSD Supported | Max Network Bandwidth (Gbps) |
|---|---|---|---|---|---|---|
| a2-highgpu-1g | 1 | 40 | 12 | 85 | Yes | 24 |
You can find more details about the machine type here.
Training Results
| Training Loss | Step | Validation Loss | Wer |
|---|---|---|---|
| 0.2128 | 1000 | 0.251406 | 17.495011 |
| 0.0270 | 2000 | 0.289191 | 17.921945 |
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