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simran14
/
mr-val-j

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Marathi
whisper
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
mr-val-j
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---
library_name: transformers
language:
- mr
base_model: simran14/mr-val-i
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: simrank14 Whisper small val j
  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: 0.9319317080444345
---

<!-- 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 val j

This model is a fine-tuned version of [simran14/mr-val-i](https://huggingface.co/simran14/mr-val-i) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2062
- Wer: 0.9319

## 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.1987        | 1.0152 | 200  | 0.1995          | 1.0835 |
| 0.1482        | 2.0305 | 400  | 0.2078          | 1.0115 |
| 0.0869        | 3.0457 | 600  | 0.2062          | 0.9319 |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1