metadata
license: apache-2.0
base_model: facebook/wav2vec2-lv-60-espeak-cv-ft
tags:
- generated_from_trainer
datasets:
- voxpopuli
metrics:
- wer
model-index:
- name: cs2fi_wav2vec2-large-xls-r-300m-czech-colab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: voxpopuli
type: voxpopuli
config: fi
split: test
args: fi
metrics:
- name: Wer
type: wer
value: 1.1551362683438156
cs2fi_wav2vec2-large-xls-r-300m-czech-colab
This model is a fine-tuned version of facebook/wav2vec2-lv-60-espeak-cv-ft on the voxpopuli dataset. It achieves the following results on the evaluation set:
- Loss: 464.4552
- Wer: 1.1551
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 934.7989 | 14.04 | 400 | 248.4365 | 0.8700 |
| 123.7719 | 28.07 | 800 | 352.9212 | 1.0063 |
| 63.0159 | 42.11 | 1200 | 464.4552 | 1.1551 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0