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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-Yfreq_speed_pause
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-Yfreq_speed_pause
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the aihub old30 adult freq pause changed dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1841
- Cer: 4.9930
## 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 |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.2772 | 0.1289 | 100 | 0.2544 | 6.4145 |
| 0.166 | 0.2579 | 200 | 0.2291 | 6.5143 |
| 0.1593 | 0.3868 | 300 | 0.2266 | 6.0855 |
| 0.1453 | 0.5158 | 400 | 0.2137 | 6.1090 |
| 0.1141 | 0.6447 | 500 | 0.2080 | 5.7507 |
| 0.1142 | 0.7737 | 600 | 0.1980 | 5.2984 |
| 0.1159 | 0.9026 | 700 | 0.1985 | 5.6391 |
| 0.0568 | 1.0316 | 800 | 0.1871 | 4.8990 |
| 0.0471 | 1.1605 | 900 | 0.1883 | 5.0047 |
| 0.0434 | 1.2895 | 1000 | 0.1893 | 4.9636 |
| 0.0408 | 1.4184 | 1100 | 0.1883 | 5.0164 |
| 0.0383 | 1.5474 | 1200 | 0.1861 | 5.0341 |
| 0.0402 | 1.6763 | 1300 | 0.1865 | 5.0987 |
| 0.0367 | 1.8053 | 1400 | 0.1854 | 4.9636 |
| 0.0386 | 1.9342 | 1500 | 0.1841 | 4.9930 |
### Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1
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