metadata
tags:
- generated_from_trainer
datasets:
- common_voice_1_0
metrics:
- wer
model-index:
- name: fineturning-without-pretraining
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: 1.1837902495797232
fineturning-without-pretraining
This model is a fine-tuned version of on the common_voice_1_0 dataset. It achieves the following results on the evaluation set:
- Loss: 812.3214
- Wer: 1.1838
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: 5e-05
- train_batch_size: 16
- 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: 500
- num_epochs: 25
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2141.1597 | 2.15 | 500 | 908.3237 | 1.0 |
| 1549.364 | 4.29 | 1000 | 813.9642 | 1.1682 |
| 1442.1247 | 6.44 | 1500 | 788.9472 | 1.5341 |
| 1395.3347 | 8.58 | 2000 | 757.5609 | 1.2662 |
| 1344.5591 | 10.73 | 2500 | 751.7140 | 1.1790 |
| 1289.6164 | 12.88 | 3000 | 746.7259 | 1.2651 |
| 1248.0024 | 15.02 | 3500 | 761.1828 | 1.2634 |
| 1208.4588 | 17.17 | 4000 | 789.4526 | 1.1426 |
| 1162.758 | 19.31 | 4500 | 794.2302 | 1.1521 |
| 1118.2571 | 21.46 | 5000 | 803.2517 | 1.2117 |
| 1097.6801 | 23.61 | 5500 | 812.3214 | 1.1838 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2