metadata
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: model_finetuned
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: ru
split: test
args: ru
metrics:
- name: Wer
type: wer
value: 0.5240747438215793
model_finetuned
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4337
- Wer: 0.5241
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: 24
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.1665 | 1.9139 | 400 | 1.3007 | 0.9612 |
| 0.9389 | 3.8278 | 800 | 0.6428 | 0.7616 |
| 0.5785 | 5.7416 | 1200 | 0.5126 | 0.6447 |
| 0.4408 | 7.6555 | 1600 | 0.4807 | 0.5937 |
| 0.3589 | 9.5694 | 2000 | 0.4581 | 0.5665 |
| 0.3033 | 11.4833 | 2400 | 0.4461 | 0.5416 |
| 0.2678 | 13.3971 | 2800 | 0.4337 | 0.5241 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1