File size: 2,014 Bytes
79c6daa |
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 74 |
---
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper_finetune
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_finetune
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the aihub_2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3508
- Cer: 12.0915
- Wer: 35.6445
## 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: 32
- eval_batch_size: 16
- 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 | Cer | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:-------:|:---------------:|:-------:|
| 0.3416 | 0.32 | 500 | 12.9022 | 0.3510 | 36.6764 |
| 0.3344 | 0.64 | 1000 | 12.7008 | 0.3562 | 36.9463 |
| 0.3119 | 0.96 | 1500 | 12.4164 | 0.3517 | 36.5065 |
| 0.246 | 1.28 | 2000 | 12.4510 | 0.3569 | 36.4665 |
| 0.2437 | 1.6 | 2500 | 12.0823 | 0.3487 | 36.0543 |
| 0.2318 | 1.92 | 3000 | 0.3454 | 11.9698 | 35.7519 |
| 0.1861 | 2.24 | 3500 | 0.3501 | 11.9882 | 35.6895 |
| 0.1729 | 2.56 | 4000 | 0.3508 | 12.0915 | 35.6445 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.15.0
- Tokenizers 0.15.0
|