|
--- |
|
language: |
|
- ko |
|
license: apache-2.0 |
|
base_model: openai/whisper-medium |
|
tags: |
|
- hf-asr-leaderboard |
|
- generated_from_trainer |
|
datasets: |
|
- Marcusxx/gwanju4 |
|
model-index: |
|
- name: gwanju4_test__model |
|
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. --> |
|
|
|
# gwanju4_test__model |
|
|
|
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Marcusxx/gwanju4 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.5722 |
|
- Cer: 275.0 |
|
|
|
## 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 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 250 |
|
- training_steps: 1000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Cer | |
|
|:-------------:|:------:|:----:|:---------------:|:-----:| |
|
| 1.9955 | 50.0 | 50 | 4.8936 | 425.0 | |
|
| 0.3976 | 100.0 | 100 | 2.6194 | 275.0 | |
|
| 0.0001 | 150.0 | 150 | 2.5074 | 275.0 | |
|
| 0.0 | 200.0 | 200 | 2.4715 | 325.0 | |
|
| 0.0 | 250.0 | 250 | 2.4384 | 325.0 | |
|
| 0.0 | 300.0 | 300 | 2.3972 | 275.0 | |
|
| 0.0 | 350.0 | 350 | 2.3937 | 275.0 | |
|
| 0.0 | 400.0 | 400 | 2.4084 | 275.0 | |
|
| 0.0 | 450.0 | 450 | 2.4310 | 275.0 | |
|
| 0.0 | 500.0 | 500 | 2.4561 | 275.0 | |
|
| 0.0 | 550.0 | 550 | 2.4782 | 275.0 | |
|
| 0.0 | 600.0 | 600 | 2.5006 | 275.0 | |
|
| 0.0 | 650.0 | 650 | 2.5150 | 275.0 | |
|
| 0.0 | 700.0 | 700 | 2.5310 | 275.0 | |
|
| 0.0 | 750.0 | 750 | 2.5415 | 275.0 | |
|
| 0.0 | 800.0 | 800 | 2.5517 | 275.0 | |
|
| 0.0 | 850.0 | 850 | 2.5592 | 275.0 | |
|
| 0.0 | 900.0 | 900 | 2.5674 | 275.0 | |
|
| 0.0 | 950.0 | 950 | 2.5723 | 275.0 | |
|
| 0.0 | 1000.0 | 1000 | 2.5722 | 275.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.2.2+cu121 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.19.1 |
|
|
