|
---
|
|
base_model: openai/whisper-tiny
|
|
tags:
|
|
- generated_from_trainer
|
|
datasets:
|
|
- audiofolder
|
|
metrics:
|
|
- wer
|
|
model-index:
|
|
- name: whisper-tiny-300v2
|
|
results:
|
|
- task:
|
|
name: Automatic Speech Recognition
|
|
type: automatic-speech-recognition
|
|
dataset:
|
|
name: audiofolder
|
|
type: audiofolder
|
|
config: default
|
|
split: test
|
|
args: default
|
|
metrics:
|
|
- name: Wer
|
|
type: wer
|
|
value: 86.48648648648648
|
|
---
|
|
|
|
<!-- 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-300v2
|
|
|
|
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the audiofolder dataset.
|
|
It achieves the following results on the evaluation set:
|
|
- Loss: 1.4117
|
|
- Wer Ortho: 83.7838
|
|
- Wer: 86.4865
|
|
|
|
## 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: 16
|
|
- seed: 42
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
|
- lr_scheduler_type: constant_with_warmup
|
|
- lr_scheduler_warmup_steps: 30
|
|
- training_steps: 300
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
|
|
| 0.2322 | 20.0 | 60 | 1.3194 | 83.7838 | 83.7838 |
|
|
| 0.0267 | 40.0 | 120 | 1.3785 | 81.0811 | 81.0811 |
|
|
| 0.0002 | 60.0 | 180 | 1.3838 | 81.0811 | 81.0811 |
|
|
| 0.0001 | 80.0 | 240 | 1.4049 | 83.7838 | 83.7838 |
|
|
| 0.0 | 100.0 | 300 | 1.4117 | 83.7838 | 86.4865 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.41.2
|
|
- Pytorch 2.3.0+cu121
|
|
- Datasets 2.19.1
|
|
- Tokenizers 0.19.1
|
|
|
