Whisper Medium Custom Hi - Nikhil Bhargava
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0 hi dataset. It achieves the following results on the evaluation set:
- Loss: 0.3972
- Wer: 0.2487
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0282 | 4.89 | 1000 | 0.2700 | 0.2647 |
0.0025 | 9.78 | 2000 | 0.3434 | 0.2554 |
0.0001 | 14.67 | 3000 | 0.3640 | 0.2471 |
0.0 | 19.56 | 4000 | 0.3902 | 0.2494 |
0.0 | 24.45 | 5000 | 0.3972 | 0.2487 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
- Downloads last month
- 17
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for nikhilbh/whisper-medium-custom-hi
Base model
openai/whisper-mediumDataset used to train nikhilbh/whisper-medium-custom-hi
Evaluation results
- Wer on mozilla-foundation/common_voice_11_0 hitest set self-reported0.249