metadata
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-meduim-mongolian
results: []
datasets:
- Cafet/whisper-mongolian-final
language:
- mn
library_name: transformers
pipeline_tag: automatic-speech-recognition
whisper-meduim-mongolian
This model is a fine-tuned version of openai/whisper-medium on custom. It achieves the following results on the evaluation set:
- Loss: 0.3098
- Wer: 26.8664
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 4
- 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: 2000
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3034 | 0.9398 | 2000 | 0.4135 | 45.1152 |
| 0.1443 | 1.8797 | 4000 | 0.3127 | 35.3290 |
| 0.0618 | 2.8195 | 6000 | 0.3038 | 31.0534 |
| 0.0179 | 3.7594 | 8000 | 0.3042 | 28.3673 |
| 0.0028 | 4.6992 | 10000 | 0.3098 | 26.8664 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.0
- Datasets 2.19.0
- Tokenizers 0.19.1