File size: 2,605 Bytes
0109c83 c219b3f 0109c83 c219b3f 0109c83 0d0f9a6 3005f57 0109c83 7b81f3b 0109c83 |
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 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 |
---
language:
- ko
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: Whisper Small Ko(FLUERS) - by p4b
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: google/fleurs ko_kr
type: google/fleurs
config: ko_kr
split: test
metrics:
- name: Wer
type: wer
value: 20.251271313191744
---
<!-- 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 Small Ko(FLUERS) - by p4b
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the FLUERS Korean dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2893
- Wer: 19.2
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
### Dataset filtering
Some of datas from FLUERS are not used for training and evaluation.
Most of filtered datas are not fit to model or including non-korean symbols.
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-07
- train_batch_size: 96
- eval_batch_size: 64
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3016 | 32.0 | 800 | 0.4048 | 140.4726 |
| 0.0451 | 64.0 | 1600 | 0.2893 | 19.2043 |
| 0.0169 | 96.0 | 2400 | 0.3110 | 20.2513 |
| 0.0092 | 128.0 | 3200 | 0.3240 | 20.0419 |
| 0.0062 | 160.0 | 4000 | 0.3335 | 20.0419 |
| 0.0045 | 192.0 | 4800 | 0.3416 | 20.0718 |
| 0.0035 | 224.0 | 5600 | 0.3501 | 20.1615 |
| 0.0028 | 256.0 | 6400 | 0.3562 | 20.3709 |
| 0.0024 | 288.0 | 7200 | 0.3618 | 20.0120 |
| 0.002 | 320.0 | 8000 | 0.3669 | 20.1017 |
| 0.0017 | 352.0 | 8800 | 0.3704 | 20.1914 |
| 0.0017 | 384.0 | 9600 | 0.3723 | 20.2513 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.14.0.dev20221208+cu116
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|