metadata
license: cc-by-nc-4.0
base_model: facebook/mms-1b-l1107
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: 0.9929506545820745
wav2vec2-large-mms-1b-korean-colab
This model is a fine-tuned version of facebook/mms-1b-l1107 on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 7.8135
- Wer: 0.9930
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 |
---|---|---|---|---|
10.9747 | 2.63 | 100 | 7.8812 | 0.9990 |
5.9431 | 5.26 | 200 | 8.2212 | 0.9960 |
5.7372 | 7.89 | 300 | 8.1054 | 0.9930 |
5.2582 | 10.53 | 400 | 8.2347 | 0.9940 |
3.8725 | 13.16 | 500 | 7.7536 | 0.9940 |
3.4454 | 15.79 | 600 | 7.7220 | 0.9930 |
2.5989 | 18.42 | 700 | 7.8135 | 0.9930 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3