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---
language:
- hi
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
- cer
model-index:
- name: 'shivam/wav2vec2-xls-r-hindi'
results:
- task:
type: 'automatic-speech-recognition'
name: 'Speech Recognition'
dataset:
type: 'mozilla-foundation/common_voice_7_0'
name: 'Common Voice Corpus 7.0'
args: 'hi'
metrics:
- type: 'wer'
- type: 'cer'
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/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: 1.2282
- Wer: 0.6838
## Evaluation results on Common Voice 7 "test" (Running ./eval.py):
### Without LM
- WER: 0.41
- CER: 0.16
## 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: 7.5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 2000
- num_epochs: 50.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.3155 | 3.4 | 500 | 4.5582 | 1.0 |
| 3.3369 | 6.8 | 1000 | 3.4269 | 1.0 |
| 2.1785 | 10.2 | 1500 | 1.7191 | 0.8831 |
| 1.579 | 13.6 | 2000 | 1.3604 | 0.7647 |
| 1.3773 | 17.01 | 2500 | 1.2737 | 0.7519 |
| 1.3165 | 20.41 | 3000 | 1.2457 | 0.7401 |
| 1.2274 | 23.81 | 3500 | 1.3617 | 0.7301 |
| 1.1787 | 27.21 | 4000 | 1.2068 | 0.7010 |
| 1.1467 | 30.61 | 4500 | 1.2416 | 0.6946 |
| 1.0801 | 34.01 | 5000 | 1.2312 | 0.6990 |
| 1.0709 | 37.41 | 5500 | 1.2984 | 0.7138 |
| 1.0307 | 40.81 | 6000 | 1.2049 | 0.6871 |
| 1.0003 | 44.22 | 6500 | 1.1956 | 0.6841 |
| 1.004 | 47.62 | 7000 | 1.2101 | 0.6793 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu113
- Datasets 1.18.1.dev0
- Tokenizers 0.11.0
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