metadata
base_model: facebook/wav2vec2-xls-r-300m
datasets:
- common_voice_11_0
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xls-r-300m-Hindi
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: hi
split: test
args: hi
metrics:
- type: wer
value: 0.5158313579410768
name: Wer
wav2vec2-large-xls-r-300m-Hindi
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7786
- Wer: 0.5158
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 6.0146 | 0.7214 | 400 | 2.8409 | 0.9970 |
| 1.2129 | 1.4427 | 800 | 1.1656 | 0.7795 |
| 0.7592 | 2.1641 | 1200 | 1.0091 | 0.7199 |
| 0.5798 | 2.8855 | 1600 | 0.9187 | 0.6614 |
| 0.4609 | 3.6069 | 2000 | 0.8386 | 0.6084 |
| 0.3828 | 4.3282 | 2400 | 0.8442 | 0.6097 |
| 0.3242 | 5.0496 | 2800 | 0.7907 | 0.5744 |
| 0.2619 | 5.7710 | 3200 | 0.7661 | 0.5485 |
| 0.2132 | 6.4923 | 3600 | 0.7943 | 0.5388 |
| 0.1911 | 7.2137 | 4000 | 0.7835 | 0.5278 |
| 0.1637 | 7.9351 | 4400 | 0.7786 | 0.5158 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1