metadata
language:
- hi
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- robust-speech-event
- generated_from_trainer
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: ''
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7.0
type: mozilla-foundation/common_voice_7_0
args: hi
metrics:
- name: Test WER
type: wer
value: 38.18
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - HI dataset. It achieves the following results on the evaluation set:
- Loss: 0.7346
- Wer: 1.0479
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: 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
- training_steps: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 1.36 | 400 | 1.4595 | 1.0039 |
| 4.7778 | 2.71 | 800 | 0.8082 | 1.0115 |
| 0.6408 | 4.07 | 1200 | 0.7032 | 1.0079 |
| 0.3937 | 5.42 | 1600 | 0.6889 | 1.0433 |
| 0.3 | 6.78 | 2000 | 0.6820 | 1.0069 |
| 0.3 | 8.14 | 2400 | 0.6670 | 1.0196 |
| 0.226 | 9.49 | 2800 | 0.7216 | 1.0422 |
| 0.197 | 10.85 | 3200 | 0.7669 | 1.0534 |
| 0.165 | 12.2 | 3600 | 0.7517 | 1.0200 |
| 0.1486 | 13.56 | 4000 | 0.7125 | 1.0357 |
| 0.1486 | 14.92 | 4400 | 0.7447 | 1.0347 |
| 0.122 | 16.27 | 4800 | 0.6899 | 1.0440 |
| 0.1069 | 17.63 | 5200 | 0.7212 | 1.0350 |
| 0.0961 | 18.98 | 5600 | 0.7417 | 1.0408 |
| 0.086 | 20.34 | 6000 | 0.7402 | 1.0356 |
| 0.086 | 21.69 | 6400 | 0.7761 | 1.0420 |
| 0.0756 | 23.05 | 6800 | 0.7346 | 1.0369 |
| 0.0666 | 24.41 | 7200 | 0.7506 | 1.0449 |
| 0.0595 | 25.76 | 7600 | 0.7319 | 1.0476 |
| 0.054 | 27.12 | 8000 | 0.7346 | 1.0479 |
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0