metadata
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- zeroth_korean
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-fine-tune_korean_byAILAB
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: zeroth_korean
type: zeroth_korean
config: clean
split: test
args: clean
metrics:
- name: Wer
type: wer
value: 0.8577021532901672
wav2vec2-large-xlsr-53-fine-tune_korean_byAILAB
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the zeroth_korean dataset. It achieves the following results on the evaluation set:
- Loss: 1.4406
- Wer: 0.8577
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: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0.99 | 38 | 54.3133 | 1.0 |
| No log | 2.0 | 77 | 33.5397 | 1.0 |
| No log | 2.99 | 115 | 19.6459 | 1.0 |
| No log | 4.0 | 154 | 11.1346 | 1.0 |
| No log | 4.99 | 192 | 5.8854 | 1.0 |
| No log | 6.0 | 231 | 4.8784 | 1.0 |
| No log | 6.99 | 269 | 4.8369 | 1.0 |
| No log | 8.0 | 308 | 4.8535 | 1.0 |
| No log | 8.99 | 346 | 4.8388 | 1.0 |
| No log | 10.0 | 385 | 4.8360 | 1.0 |
| 15.1801 | 10.99 | 423 | 4.7653 | 1.0 |
| 15.1801 | 12.0 | 462 | 4.7385 | 1.0 |
| 15.1801 | 12.99 | 500 | 4.6927 | 0.9989 |
| 15.1801 | 14.0 | 539 | 4.6673 | 0.9991 |
| 15.1801 | 14.99 | 577 | 4.6948 | 0.9991 |
| 15.1801 | 16.0 | 616 | 4.6713 | 0.9991 |
| 15.1801 | 16.99 | 654 | 4.6603 | 1.0 |
| 15.1801 | 18.0 | 693 | 4.6428 | 0.9995 |
| 15.1801 | 18.99 | 731 | 4.6520 | 0.9994 |
| 15.1801 | 20.0 | 770 | 4.6554 | 0.9967 |
| 4.3888 | 20.99 | 808 | 4.6054 | 0.9998 |
| 4.3888 | 22.0 | 847 | 4.5723 | 0.9976 |
| 4.3888 | 22.99 | 885 | 4.4586 | 0.9967 |
| 4.3888 | 24.0 | 924 | 4.2547 | 0.9934 |
| 4.3888 | 24.99 | 962 | 3.6554 | 0.9931 |
| 4.3888 | 26.0 | 1001 | 2.8387 | 1.0084 |
| 4.3888 | 26.99 | 1039 | 2.4191 | 1.0551 |
| 4.3888 | 28.0 | 1078 | 2.0997 | 1.0197 |
| 4.3888 | 28.99 | 1116 | 2.0103 | 1.0176 |
| 4.3888 | 30.0 | 1155 | 1.8189 | 0.9461 |
| 4.3888 | 30.99 | 1193 | 1.7623 | 0.9726 |
| 2.7217 | 32.0 | 1232 | 1.7383 | 0.9976 |
| 2.7217 | 32.99 | 1270 | 1.6522 | 0.9584 |
| 2.7217 | 34.0 | 1309 | 1.5558 | 0.9193 |
| 2.7217 | 34.99 | 1347 | 1.5811 | 0.9440 |
| 2.7217 | 36.0 | 1386 | 1.5208 | 0.9158 |
| 2.7217 | 36.99 | 1424 | 1.5088 | 0.9038 |
| 2.7217 | 38.0 | 1463 | 1.5039 | 0.9086 |
| 2.7217 | 38.99 | 1501 | 1.4853 | 0.8987 |
| 2.7217 | 40.0 | 1540 | 1.4799 | 0.8847 |
| 2.7217 | 40.99 | 1578 | 1.4259 | 0.8694 |
| 0.7635 | 42.0 | 1617 | 1.4878 | 0.8883 |
| 0.7635 | 42.99 | 1655 | 1.4394 | 0.8693 |
| 0.7635 | 44.0 | 1694 | 1.4623 | 0.8743 |
| 0.7635 | 44.99 | 1732 | 1.4495 | 0.8710 |
| 0.7635 | 46.0 | 1771 | 1.4463 | 0.8655 |
| 0.7635 | 46.99 | 1809 | 1.4553 | 0.8704 |
| 0.7635 | 48.0 | 1848 | 1.4500 | 0.8646 |
| 0.7635 | 48.99 | 1886 | 1.4387 | 0.8566 |
| 0.7635 | 49.35 | 1900 | 1.4406 | 0.8577 |
Framework versions
- Transformers 4.33.2
- Pytorch 1.12.1
- Datasets 2.14.5
- Tokenizers 0.13.3