---
language:
- mr
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_9_0
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_9_0
metrics:
- wer
model-index:
- name: XLS-R-300M - Marathi
  results:
  - task:
      type: automatic-speech-recognition
      name: Speech Recognition
    dataset:
      type: mozilla-foundation/common_voice_9_0
      name: Common Voice 9
      args: mr
    metrics:
    - type: wer
      value: 23.841
      name: Test WER
    - name: Test CER
      type: cer
      value: 5.522
---

<!-- 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_9_0 - MR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3642
- Wer: 0.4190
- Cer: 0.0946

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 6124
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| 3.5184        | 12.9   | 400  | 3.4210          | 1.0    | 1.0    |
| 2.3797        | 25.81  | 800  | 1.1068          | 0.8389 | 0.2584 |
| 1.5022        | 38.71  | 1200 | 0.5278          | 0.6280 | 0.1517 |
| 1.3181        | 51.61  | 1600 | 0.4254          | 0.5587 | 0.1297 |
| 1.2037        | 64.52  | 2000 | 0.3836          | 0.5143 | 0.1176 |
| 1.1245        | 77.42  | 2400 | 0.3643          | 0.4871 | 0.1111 |
| 1.0582        | 90.32  | 2800 | 0.3562          | 0.4676 | 0.1062 |
| 1.0027        | 103.23 | 3200 | 0.3530          | 0.4625 | 0.1058 |
| 0.9382        | 116.13 | 3600 | 0.3388          | 0.4442 | 0.1002 |
| 0.8915        | 129.03 | 4000 | 0.3430          | 0.4427 | 0.1000 |
| 0.853         | 141.94 | 4400 | 0.3536          | 0.4375 | 0.1000 |
| 0.8127        | 154.84 | 4800 | 0.3511          | 0.4344 | 0.0986 |
| 0.7861        | 167.74 | 5200 | 0.3595          | 0.4372 | 0.0993 |
| 0.7619        | 180.65 | 5600 | 0.3628          | 0.4316 | 0.0985 |
| 0.7537        | 193.55 | 6000 | 0.3633          | 0.4174 | 0.0943 |


### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.1.1.dev0
- Tokenizers 0.12.1