---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-fl102
tags:
- generated_from_trainer
datasets:
- common_voice_6_1
metrics:
- wer
model-index:
- name: wav2vec2-large-mms-1b-hindi-colab
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_6_1
      type: common_voice_6_1
      config: hi
      split: test
      args: hi
    metrics:
    - name: Wer
      type: wer
      value: 0.32018561484918795
---

<!-- 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-mms-1b-hindi-colab

This model is a fine-tuned version of [facebook/mms-1b-fl102](https://huggingface.co/facebook/mms-1b-fl102) on the common_voice_6_1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3535
- Wer: 0.3202

## 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: 0.001
- train_batch_size: 4
- 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: 10
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 16.7585       | 0.14  | 10   | 10.2106         | 2.0951 |
| 6.9602        | 0.27  | 20   | 3.7700          | 1.0046 |
| 2.4653        | 0.41  | 30   | 1.3321          | 0.6763 |
| 1.0919        | 0.55  | 40   | 0.6594          | 0.4664 |
| 0.7645        | 0.68  | 50   | 0.4930          | 0.3910 |
| 0.8434        | 0.82  | 60   | 0.4819          | 0.3898 |
| 0.5118        | 0.96  | 70   | 0.4492          | 0.3817 |
| 0.6097        | 1.1   | 80   | 0.4299          | 0.4327 |
| 0.4698        | 1.23  | 90   | 0.4308          | 0.3643 |
| 0.5402        | 1.37  | 100  | 0.4042          | 0.4107 |
| 0.5622        | 1.51  | 110  | 0.4156          | 0.3701 |
| 0.4084        | 1.64  | 120  | 0.4138          | 0.3701 |
| 0.4888        | 1.78  | 130  | 0.3917          | 0.3434 |
| 0.4253        | 1.92  | 140  | 0.3852          | 0.3457 |
| 0.5004        | 2.05  | 150  | 0.3843          | 0.3364 |
| 0.3791        | 2.19  | 160  | 0.3841          | 0.3469 |
| 0.3302        | 2.33  | 170  | 0.3764          | 0.3271 |
| 0.4047        | 2.47  | 180  | 0.3689          | 0.3364 |
| 0.2951        | 2.6   | 190  | 0.3657          | 0.3329 |
| 0.3545        | 2.74  | 200  | 0.3582          | 0.3306 |
| 0.3736        | 2.88  | 210  | 0.3585          | 0.3248 |
| 0.388         | 3.01  | 220  | 0.3602          | 0.3237 |
| 0.2997        | 3.15  | 230  | 0.3624          | 0.3167 |
| 0.3704        | 3.29  | 240  | 0.3625          | 0.3190 |
| 0.2095        | 3.42  | 250  | 0.3571          | 0.3248 |
| 0.3564        | 3.56  | 260  | 0.3570          | 0.3202 |
| 0.2119        | 3.7   | 270  | 0.3550          | 0.3225 |
| 0.3697        | 3.84  | 280  | 0.3542          | 0.3190 |
| 0.3551        | 3.97  | 290  | 0.3535          | 0.3202 |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3