metadata
language:
- ur
license: apache-2.0
tags:
- automatic-speech-recognition
- robust-speech-event
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
metrics:
- wer
- cer
base_model: Harveenchadha/vakyansh-wav2vec2-urdu-urm-60
model-index:
- name: wav2vec2-urdu-V8-Abid
results:
- task:
type: automatic-speech-recognition
name: Speech Recognition
dataset:
name: Common Voice ur
type: mozilla-foundation/common_voice_8_0
args: ur
metrics:
- type: wer
value: 44.63
name: Test WER
- type: cer
value: 18.82
name: Test CER
wav2vec2-60-Urdu-V8
This model is a fine-tuned version of Harveenchadha/vakyansh-wav2vec2-urdu-urm-60 on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 11.4832
- Wer: 0.5729
- Cer: 0.3170
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 7.5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 19.671 | 8.33 | 100 | 7.7671 | 0.8795 | 0.4492 |
| 2.085 | 16.67 | 200 | 9.2759 | 0.6201 | 0.3320 |
| 0.6633 | 25.0 | 300 | 8.7025 | 0.5738 | 0.3104 |
| 0.388 | 33.33 | 400 | 10.2286 | 0.5852 | 0.3128 |
| 0.2822 | 41.67 | 500 | 11.1953 | 0.5738 | 0.3174 |
| 0.2293 | 50.0 | 600 | 11.4832 | 0.5729 | 0.3170 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0