metadata
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-korean
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: ko
split: test
args: ko
metrics:
- name: Wer
type: wer
value: 0.5931520644511581
wav2vec2-large-xls-r-300m-korean
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.4687
- Wer: 0.5932
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: 0.0003
- 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: 500
- num_epochs: 300
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 20.8922 | 6.25 | 400 | 4.6827 | 0.9990 |
| 4.0513 | 12.5 | 800 | 2.3657 | 0.9204 |
| 1.5386 | 18.75 | 1200 | 1.2355 | 0.7392 |
| 0.7429 | 25.0 | 1600 | 1.1179 | 0.6636 |
| 0.3746 | 31.25 | 2000 | 1.0465 | 0.6314 |
| 0.2407 | 37.5 | 2400 | 1.1492 | 0.6596 |
| 0.1966 | 43.75 | 2800 | 1.1291 | 0.6344 |
| 0.1697 | 50.0 | 3200 | 1.1897 | 0.6395 |
| 0.1533 | 56.25 | 3600 | 1.2202 | 0.6193 |
| 0.129 | 62.5 | 4000 | 1.2106 | 0.6516 |
| 0.1097 | 68.75 | 4400 | 1.1662 | 0.6254 |
| 0.102 | 75.0 | 4800 | 1.2086 | 0.6133 |
| 0.0918 | 81.25 | 5200 | 1.2295 | 0.6485 |
| 0.0806 | 87.5 | 5600 | 1.2861 | 0.6123 |
| 0.0738 | 93.75 | 6000 | 1.2436 | 0.6093 |
| 0.0697 | 100.0 | 6400 | 1.3496 | 0.6626 |
| 0.0667 | 106.25 | 6800 | 1.2364 | 0.6133 |
| 0.0591 | 112.5 | 7200 | 1.2689 | 0.6062 |
| 0.054 | 118.75 | 7600 | 1.2886 | 0.6183 |
| 0.0523 | 125.0 | 8000 | 1.3328 | 0.6445 |
| 0.0542 | 131.25 | 8400 | 1.4019 | 0.6133 |
| 0.045 | 137.5 | 8800 | 1.3426 | 0.6042 |
| 0.0425 | 143.75 | 9200 | 1.3042 | 0.6032 |
| 0.0378 | 150.0 | 9600 | 1.3638 | 0.6224 |
| 0.0354 | 156.25 | 10000 | 1.3397 | 0.6294 |
| 0.0282 | 162.5 | 10400 | 1.3939 | 0.6173 |
| 0.0288 | 168.75 | 10800 | 1.3674 | 0.6475 |
| 0.0278 | 175.0 | 11200 | 1.3636 | 0.6324 |
| 0.0239 | 181.25 | 11600 | 1.4101 | 0.6405 |
| 0.0238 | 187.5 | 12000 | 1.4528 | 0.6163 |
| 0.0214 | 193.75 | 12400 | 1.4458 | 0.6093 |
| 0.0194 | 200.0 | 12800 | 1.3920 | 0.6304 |
| 0.0168 | 206.25 | 13200 | 1.4277 | 0.6193 |
| 0.0168 | 212.5 | 13600 | 1.3959 | 0.6203 |
| 0.0154 | 218.75 | 14000 | 1.4043 | 0.6133 |
| 0.0144 | 225.0 | 14400 | 1.4508 | 0.6193 |
| 0.0134 | 231.25 | 14800 | 1.4309 | 0.6224 |
| 0.0109 | 237.5 | 15200 | 1.4301 | 0.6123 |
| 0.0107 | 243.75 | 15600 | 1.4373 | 0.6002 |
| 0.0098 | 250.0 | 16000 | 1.4147 | 0.6113 |
| 0.0095 | 256.25 | 16400 | 1.4585 | 0.6193 |
| 0.009 | 262.5 | 16800 | 1.4424 | 0.6203 |
| 0.0079 | 268.75 | 17200 | 1.5019 | 0.6193 |
| 0.0066 | 275.0 | 17600 | 1.4835 | 0.5932 |
| 0.0059 | 281.25 | 18000 | 1.4749 | 0.5992 |
| 0.0057 | 287.5 | 18400 | 1.4897 | 0.6002 |
| 0.0053 | 293.75 | 18800 | 1.4667 | 0.5901 |
| 0.0048 | 300.0 | 19200 | 1.4687 | 0.5932 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 1.12.1
- Datasets 2.14.5
- Tokenizers 0.14.0