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---
language:
- te
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- Chai_Bisket_Stories_16-08-2021_14-17
metrics:
- wer
model-index:
- name: Whisper Small Telugu - Naga Budigam
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Chai_Bisket_Stories_16-08-2021_14-17
type: Chai_Bisket_Stories_16-08-2021_14-17
config: None
split: None
args: 'config: te, split: test'
metrics:
- name: Wer
type: wer
value: 77.48711850971065
---
<!-- 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. -->
# Whisper Small Telugu - Naga Budigam
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Chai_Bisket_Stories_16-08-2021_14-17 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7063
- Wer: 77.4871
## 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: 1e-05
- train_batch_size: 16
- 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2933 | 2.62 | 500 | 0.3849 | 86.6429 |
| 0.0692 | 5.24 | 1000 | 0.3943 | 82.7190 |
| 0.0251 | 7.85 | 1500 | 0.4720 | 82.4415 |
| 0.0098 | 10.47 | 2000 | 0.5359 | 81.6092 |
| 0.0061 | 13.09 | 2500 | 0.5868 | 75.9413 |
| 0.0025 | 15.71 | 3000 | 0.6235 | 76.6944 |
| 0.0009 | 18.32 | 3500 | 0.6634 | 78.3987 |
| 0.0005 | 20.94 | 4000 | 0.6776 | 77.1700 |
| 0.0002 | 23.56 | 4500 | 0.6995 | 78.2798 |
| 0.0001 | 26.18 | 5000 | 0.7063 | 77.4871 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1
- Tokenizers 0.13.2
|