File size: 2,018 Bytes
47b8c06 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 |
---
language:
- ko
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: openai/whisper-large-v2
datasets:
- Bingsu/zeroth-korean
model-index:
- name: Whisper large-v2 Korean - ML_project_voice2text
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 large-v2 Korean - ML_project_voice2text
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: 0.0646
- Cer: 1.4722
## 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: 0.001
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 16000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 0.2332 | 0.3593 | 2000 | 0.2677 | 7.6162 |
| 0.196 | 0.7186 | 4000 | 0.2293 | 6.0733 |
| 0.1524 | 1.0780 | 6000 | 0.1864 | 5.3510 |
| 0.1062 | 1.4373 | 8000 | 0.1448 | 3.4508 |
| 0.0815 | 1.7966 | 10000 | 0.1126 | 3.2428 |
| 0.0349 | 2.1559 | 12000 | 0.0863 | 1.9394 |
| 0.0281 | 2.5153 | 14000 | 0.0732 | 1.6214 |
| 0.0191 | 2.8746 | 16000 | 0.0646 | 1.4722 |
### Framework versions
- PEFT 0.11.2.dev0
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |