metadata
base_model: openai/whisper-large-v3
language:
- rus
license: apache-2.0
metrics:
- wer
tags:
- hf-asr-leaderboard
- generated_from_trainer
model-index:
- name: Whisper Large V3 rus pl - Chee Li
results: []
Whisper Large V3 rus pl - Chee Li
This model is a fine-tuned version of openai/whisper-large-v3 on the Google Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.1165
- Wer: 108.0475
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-06
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0324 | 2.6178 | 1000 | 0.0814 | 73.6269 |
| 0.0058 | 5.2356 | 2000 | 0.1047 | 117.0652 |
| 0.0033 | 7.8534 | 3000 | 0.1141 | 126.9367 |
| 0.0022 | 10.4712 | 4000 | 0.1165 | 108.0475 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1