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---
language:
- en
license: mit
base_model: distil-whisper/distil-small.en
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- vision
- finetuneasr
metrics:
- wer
model-index:
- name: ThangaTharun/finetunedsmall
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: ThangaTharun/Barishka2
type: vision
metrics:
- name: Wer
type: wer
value: 5.47945205479452
---
<!-- 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. -->
# ThangaTharun/finetunedsmall
This model is a fine-tuned version of [distil-whisper/distil-small.en](https://huggingface.co/distil-whisper/distil-small.en) on the ThangaTharun/Barishka2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0136
- Wer: 5.4795
## 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: 1
- training_steps: 60
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 3.1327 | 1.25 | 5 | 2.6560 | 47.9452 |
| 1.7171 | 2.5 | 10 | 1.7472 | 26.0274 |
| 1.0789 | 3.75 | 15 | 0.9175 | 12.3288 |
| 0.0999 | 5.0 | 20 | 0.1663 | 13.6986 |
| 0.0173 | 6.25 | 25 | 0.0855 | 13.6986 |
| 0.004 | 7.5 | 30 | 0.0366 | 9.5890 |
| 0.0017 | 8.75 | 35 | 0.0216 | 6.8493 |
| 0.0008 | 10.0 | 40 | 0.0165 | 6.8493 |
| 0.0005 | 11.25 | 45 | 0.0146 | 5.4795 |
| 0.0005 | 12.5 | 50 | 0.0138 | 5.4795 |
| 0.0005 | 13.75 | 55 | 0.0136 | 5.4795 |
| 0.0004 | 15.0 | 60 | 0.0136 | 5.4795 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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