---
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 valG
  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: 0.09443574641516936
---

<!-- 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: 0.0944

## 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 | 0.0020          | 0.1814 |
| 0.0006        | 1.2195 | 2000 | 0.0011          | 0.1069 |
| 0.0009        | 1.8293 | 3000 | 0.0009          | 0.0944 |


### Framework versions

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