metadata
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-hi-colab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: hi
split: test
args: hi
metrics:
- name: Wer
type: wer
value: 1.0222783552113959
wav2vec2-large-xls-r-300m-hi-colab
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7522
- Wer: 1.0223
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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- 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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.9636 | 0.95 | 400 | 2.2746 | 1.0338 |
| 0.9533 | 1.89 | 800 | 0.8338 | 1.0699 |
| 0.5378 | 2.84 | 1200 | 0.7781 | 1.0159 |
| 0.4041 | 3.79 | 1600 | 0.7267 | 1.0191 |
| 0.3308 | 4.73 | 2000 | 0.6780 | 1.0237 |
| 0.2728 | 5.68 | 2400 | 0.6862 | 1.0203 |
| 0.2272 | 6.63 | 2800 | 0.6658 | 1.0266 |
| 0.198 | 7.57 | 3200 | 0.6819 | 1.0306 |
| 0.1787 | 8.52 | 3600 | 0.6930 | 1.0257 |
| 0.158 | 9.47 | 4000 | 0.7278 | 1.0318 |
| 0.1391 | 10.41 | 4400 | 0.7102 | 1.0319 |
| 0.1249 | 11.36 | 4800 | 0.7726 | 1.0190 |
| 0.1131 | 12.31 | 5200 | 0.7325 | 1.0253 |
| 0.1049 | 13.25 | 5600 | 0.7512 | 1.0227 |
| 0.095 | 14.2 | 6000 | 0.7580 | 1.0222 |
| 0.0835 | 15.15 | 6400 | 0.7161 | 1.0204 |
| 0.0817 | 16.09 | 6800 | 0.7530 | 1.0239 |
| 0.0707 | 17.04 | 7200 | 0.7613 | 1.0250 |
| 0.0682 | 17.99 | 7600 | 0.7412 | 1.0196 |
| 0.0599 | 18.93 | 8000 | 0.7700 | 1.0214 |
| 0.0593 | 19.88 | 8400 | 0.7522 | 1.0223 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.2.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2