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---
library_name: transformers
language:
- mr
base_model: simran14/mr-val-f
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: simrank14 Whisper small valG3
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      config: mr
      split: test
      args: mr
    metrics:
    - name: Wer
      type: wer
      value: 0.090463
---

<!-- 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. -->

# simrank14 Whisper small valG

This model is a fine-tuned version of [simran14/mr-val-f](https://huggingface.co/simran14/mr-val-f) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0009
- Wer: 0.090463

## 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: 5e-07
- train_batch_size: 8
- 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: 100
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training Results

| Training Loss |  Epoch  |  Step  | Validation Loss |   WER    |
|:-------------:|:-------:|:------:|:---------------:|:--------:|
|    0.001      |  0.6098 |  1000  |     0.0017      | 0.154740 |
|   0.0006      |  1.2195 |  2000  |     0.0010      | 0.126172 |
|   0.0009      |  1.8293 |  3000  |     0.0008      | 0.090463 |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.1.dev0
- Tokenizers 0.19.1