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---

language:
- hi
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_15_0
- mms
- generated_from_trainer
datasets:
- common_voice_15_0
metrics:
- wer
model-index:
- name: RohitDataScienceSpeechAnalyticsOutput
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: MOZILLA-FOUNDATION/COMMON_VOICE_15_0 - HI
      type: common_voice_15_0
      config: hi
      split: validation
      args: 'Config: hi, Training split: train, Eval split: validation'
    metrics:
    - name: Wer
      type: wer
      value: 1.0016248153618907
---


<!-- 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. -->

# RohitDataScienceSpeechAnalyticsOutput

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the MOZILLA-FOUNDATION/COMMON_VOICE_15_0 - HI dataset.

It achieves the following results on the evaluation set:

- Loss: 20.2731

- Wer: 1.0016



## 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
- 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: 500
- num_epochs: 1.0

- mixed_precision_training: Native AMP



### Training results



| Training Loss | Epoch  | Step | Validation Loss | Wer    |

|:-------------:|:------:|:----:|:---------------:|:------:|

| No log        | 0.6897 | 100  | 21.9156         | 1.0006 |





### Framework versions



- Transformers 4.42.0.dev0

- Pytorch 2.3.0

- Datasets 2.19.1

- Tokenizers 0.19.1