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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