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---
library_name: transformers
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- aihub_adult_baseline
model-index:
- name: whisper-small-E50_freq_pause_speed
results: []
---
<!-- 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-E50_freq_pause_speed
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the aihub old adult freq speed pause changed dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1725
- Cer: 5.0634
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.3013 | 0.1289 | 100 | 0.2517 | 6.4438 |
| 0.1815 | 0.2579 | 200 | 0.2203 | 6.0385 |
| 0.1893 | 0.3868 | 300 | 0.2076 | 5.6450 |
| 0.1646 | 0.5158 | 400 | 0.1988 | 5.5275 |
| 0.1377 | 0.6447 | 500 | 0.1969 | 5.4453 |
| 0.1279 | 0.7737 | 600 | 0.1852 | 5.1809 |
| 0.1254 | 0.9026 | 700 | 0.1795 | 4.9107 |
| 0.0701 | 1.0309 | 800 | 0.1769 | 4.8990 |
| 0.0586 | 1.1599 | 900 | 0.1805 | 4.9518 |
| 0.0588 | 1.2888 | 1000 | 0.1763 | 5.2044 |
| 0.0568 | 1.4178 | 1100 | 0.1782 | 5.2103 |
| 0.0487 | 1.5467 | 1200 | 0.1737 | 4.8285 |
| 0.0526 | 1.6757 | 1300 | 0.1745 | 5.3571 |
| 0.0439 | 1.8046 | 1400 | 0.1730 | 7.2721 |
| 0.0476 | 1.9336 | 1500 | 0.1725 | 5.0634 |
### Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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