transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer hi dataset:aihub_elder base_model:openai/whisper-small license:apache-2.0 endpoints_compatible region:us
---
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- aihub_elder
model-index:
- name: whisper-small-ko-E50_Y_freq_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-ko-E50_Y_freq_speed

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the aihub Y dialogue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1746
- Cer: 5.4570

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4066        | 0.13  | 100  | 0.2624          | 6.2676 |
| 0.2544        | 0.26  | 200  | 0.2160          | 5.8036 |
| 0.2379        | 0.39  | 300  | 0.2100          | 5.7507 |
| 0.2078        | 0.52  | 400  | 0.1967          | 6.1325 |
| 0.1842        | 0.64  | 500  | 0.1921          | 5.4570 |
| 0.1653        | 0.77  | 600  | 0.1847          | 5.8564 |
| 0.1703        | 0.9   | 700  | 0.1809          | 5.7683 |
| 0.0863        | 1.03  | 800  | 0.1799          | 5.6743 |
| 0.0718        | 1.16  | 900  | 0.1829          | 5.1339 |
| 0.0763        | 1.29  | 1000 | 0.1772          | 5.7801 |
| 0.0709        | 1.42  | 1100 | 0.1792          | 5.6215 |
| 0.0661        | 1.55  | 1200 | 0.1748          | 4.9930 |
| 0.068         | 1.68  | 1300 | 0.1743          | 5.4100 |
| 0.0595        | 1.81  | 1400 | 0.1749          | 5.4864 |
| 0.0624        | 1.93  | 1500 | 0.1746          | 5.4570 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
