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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
|