whisper-small-id / README.md
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---
library_name: transformers
language:
- id
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- kneth90/test_data_set_2
metrics:
- wer
model-index:
- name: Whisper Small ID - Kenn
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Test Dataset 2
type: kneth90/test_data_set_2
args: 'config: hi, split: test'
metrics:
- name: Wer
type: wer
value: 62.0253164556962
---
<!-- 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 ID - Kenn
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Test Dataset 2 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5890
- Wer: 62.0253
## 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: Use OptimizerNames.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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:--------:|:----:|:---------------:|:-------:|
| 0.0012 | 41.6667 | 1000 | 1.4854 | 64.1350 |
| 0.0001 | 83.3333 | 2000 | 1.5412 | 62.2363 |
| 0.0 | 125.0 | 3000 | 1.5755 | 62.0253 |
| 0.0 | 166.6667 | 4000 | 1.5890 | 62.0253 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0