metadata
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: base
results: []
base
This model is a fine-tuned version of openai/whisper-small on the tutorial Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5910
- Wer: 95.8127
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6188 | 0.64 | 1000 | 0.6863 | 79.4283 |
| 0.3827 | 1.28 | 2000 | 0.6164 | 80.7766 |
| 0.3412 | 1.93 | 3000 | 0.5910 | 95.8127 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1