whisper-tiny / README.md
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---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: Whisper Tiny-Handy-Pretty - ckandemir
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14
type: PolyAI/minds14
config: en-US
split: train[450:]
args: en-US
metrics:
- name: Wer
type: wer
value: 0.3116883116883117
---
<!-- 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 Tiny-Handy-Pretty - ckandemir
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the PolyAI/minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5197
- Wer Ortho: 31.6471
- Wer: 0.3117
## 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: 5e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 100
- training_steps: 150
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.8427 | 1.32 | 50 | 0.5401 | 35.9655 | 0.3566 |
| 0.1982 | 2.63 | 100 | 0.5179 | 35.5336 | 0.3501 |
| 0.0531 | 3.95 | 150 | 0.5197 | 31.6471 | 0.3117 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.1
- Tokenizers 0.13.3