|
--- |
|
language: |
|
- zh |
|
base_model: openai/whisper-large_v2 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- LeoKuo49/Amitabha |
|
model-index: |
|
- name: Whisper largev2 amitabha |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# Whisper largev2 amitabha |
|
|
|
This model is a fine-tuned version of [openai/whisper-large_v2](https://huggingface.co/openai/whisper-large_v2) on the Common Voice 11.0 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0000 |
|
- Cer: 3.0142 |
|
|
|
## 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 | |
|
|:-------------:|:-------:|:----:|:---------------:|:------:| |
|
| 0.0121 | 9.1743 | 1000 | 0.0062 | 4.9920 | |
|
| 0.0002 | 18.3486 | 2000 | 0.0002 | 3.0260 | |
|
| 0.0 | 27.5229 | 3000 | 0.0001 | 3.0142 | |
|
| 0.0001 | 36.6972 | 4000 | 0.0000 | 3.0142 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.19.2 |
|
- Tokenizers 0.19.1 |
|
|
