metadata
license: cc-by-nc-4.0
base_model: weekcircle/wav2vec2-large-mms-1b-korean-colab
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-mms-1b-korean-colab
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: 0.9959718026183283
wav2vec2-large-mms-1b-korean-colab
This model is a fine-tuned version of weekcircle/wav2vec2-large-mms-1b-korean-colab on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 8.8258
- Wer: 0.9960
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.4313 | 2.63 | 100 | 7.9123 | 0.9839 |
| 2.3616 | 5.26 | 200 | 7.9118 | 0.9930 |
| 1.859 | 7.89 | 300 | 7.9977 | 0.9909 |
| 1.4135 | 10.53 | 400 | 8.3395 | 1.0040 |
| 1.1407 | 13.16 | 500 | 8.5900 | 0.9940 |
| 0.9639 | 15.79 | 600 | 8.6300 | 0.9950 |
| 0.7991 | 18.42 | 700 | 8.8258 | 0.9960 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3