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---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- wwwtwwwt/fineaudio-Education
metrics:
- wer
model-index:
- name: Whisper Tiny En - Education - Documentaries
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: fineaudio-Education-Documentaries
type: wwwtwwwt/fineaudio-Education
args: 'config: en, split: test'
metrics:
- name: Wer
type: wer
value: 46.58774235626618
---
<!-- 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 En - Education - Documentaries
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the fineaudio-Education-Documentaries dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4409
- Wer: 46.5877
## 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 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 |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.7835 | 0.8230 | 1000 | 1.3163 | 54.4973 |
| 0.5343 | 1.6461 | 2000 | 1.3817 | 50.0405 |
| 0.4552 | 2.4691 | 3000 | 1.4197 | 46.4158 |
| 0.3277 | 3.2922 | 4000 | 1.4409 | 46.5877 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.0
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