metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- common_voice_1_0
metrics:
- wer
model-index:
- name: finetuning2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_1_0
type: common_voice_1_0
config: en
split: validation
args: en
metrics:
- name: Wer
type: wer
value: 0.4213759213759214
finetuning2
This model is a fine-tuned version of facebook/wav2vec2-base on the common_voice_1_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6883
- Wer: 0.4214
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: 0.0001
- train_batch_size: 32
- 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: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.5277 | 4.27 | 500 | 2.8353 | 0.9863 |
| 1.2768 | 8.55 | 1000 | 0.7019 | 0.5581 |
| 0.4511 | 12.82 | 1500 | 0.6201 | 0.4726 |
| 0.2591 | 17.09 | 2000 | 0.6428 | 0.4469 |
| 0.1854 | 21.37 | 2500 | 0.6901 | 0.4388 |
| 0.1386 | 25.64 | 3000 | 0.6933 | 0.4259 |
| 0.111 | 29.91 | 3500 | 0.6883 | 0.4214 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2