README.md

---
language: 
- pa-IN

license: apache-2.0
tags:
- automatic-speech-recognition
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
metrics:
- wer
- cer
model-index:
- name: wav2vec2-large-xlsr-53-punjabi
  results:
  - task: 
      type: automatic-speech-recognition  # Required. Example: automatic-speech-recognition
      name: Speech Recognition  # Optional. Example: Speech Recognition
    dataset:
      type: mozilla-foundation/common_voice_7_0  # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
      name: Common Voice pa-IN  # Required. Example: Common Voice zh-CN
      args: pa-IN         # Optional. Example: zh-CN
    metrics:
      - type: wer    # Required. Example: wer
        value: 39.42  # Required. Example: 20.90
        name: Test WER    # Optional. Example: Test WER
        args: 
        - learning_rate: 0.0003
        - 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: 30
        - mixed_precision_training: Native AMP         # Optional. Example for BLEU: max_order
      - type: cer    # Required. Example: wer
        value: 12.99  # Required. Example: 20.90
        name: Test CER    # Optional. Example: Test WER
        args: 
        - learning_rate: 0.0003
        - 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: 30
        - mixed_precision_training: Native AMP         # Optional. Example for BLEU: max_order
---

<!-- 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. -->

# wav2vec2-large-xlsr-53-punjabi

This model is a fine-tuned version of [manandey/wav2vec2-large-xlsr-punjabi](https://huggingface.co/manandey/wav2vec2-large-xlsr-punjabi) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6752
- Wer: 0.3942
- Cer: 0.1299

## 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
- 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.8899        | 4.16  | 100  | 0.5338          | 0.4233 | 0.1394 |
| 0.3652        | 8.33  | 200  | 0.5759          | 0.4192 | 0.1349 |
| 0.248         | 12.49 | 300  | 0.6309          | 0.4102 | 0.1327 |
| 0.1898        | 16.65 | 400  | 0.6441          | 0.4007 | 0.1351 |
| 0.1486        | 20.82 | 500  | 0.6790          | 0.4044 | 0.1393 |
| 0.1245        | 24.98 | 600  | 0.6869          | 0.3987 | 0.1309 |
| 0.1085        | 29.16 | 700  | 0.6752          | 0.3942 | 0.1299 |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3