metadata
language:
- zh
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
datasets:
- LeoKuo49/Amitabha_all
model-index:
- name: Whisper-finetune_all
results: []
Whisper-finetune_all
This model is a fine-tuned version of openai/whisper-large-v2 on the Amitabha_all dataset. It achieves the following results on the evaluation set:
- Loss: 0.0002
- Cer: 0.1505
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: 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 | Cer |
|---|---|---|---|---|
| 0.0581 | 3.1056 | 1000 | 0.0515 | 6.2281 |
| 0.0132 | 6.2112 | 2000 | 0.0075 | 2.8061 |
| 0.0009 | 9.3168 | 3000 | 0.0006 | 0.3260 |
| 0.0001 | 12.4224 | 4000 | 0.0002 | 0.1505 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1