metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
base_model: openai/whisper-small
model-index:
- name: whisper-small-fine_tuned-ru
results: []
whisper-small-fine_tuned-ru
This model is a fine-tuned version of openai/whisper-small on the Mozilla common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2290
- Wer: 17.6336
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-07
- 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: 5000
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0286 | 0.22 | 500 | 0.2225 | 18.0199 |
0.0287 | 0.44 | 1000 | 0.2235 | 18.0455 |
0.0334 | 0.66 | 1500 | 0.2243 | 18.1956 |
0.0373 | 0.88 | 2000 | 0.2239 | 17.9803 |
0.0261 | 1.1 | 2500 | 0.2268 | 17.7674 |
0.0252 | 1.32 | 3000 | 0.2277 | 17.8221 |
0.0265 | 1.54 | 3500 | 0.2290 | 17.6336 |
0.0271 | 1.76 | 4000 | 0.2293 | 17.8279 |
0.0252 | 1.97 | 4500 | 0.2293 | 17.8744 |
0.023 | 2.19 | 5000 | 0.2298 | 17.8930 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3