output-tiny-id / README.md
TheRains's picture
Update metadata with huggingface_hub
688048e
---
language:
- id
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_12_0
metrics:
- wer
model-index:
- name: Whisper tiny ID - Augmented
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_12_0
type: mozilla-foundation/common_voice_12_0
config: id
split: test
args: id
metrics:
- type: wer
value: 14.42705294401177
name: Wer
- type: wer
value: 14.42705294401177
name: WER
---
<!-- 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 ID - Augmented
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_12_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2874
- Wer: 14.4271
## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.6729 | 0.77 | 200 | 0.4170 | 21.8473 |
| 0.5012 | 1.54 | 400 | 0.3465 | 18.2560 |
| 0.3832 | 2.31 | 600 | 0.3097 | 16.0971 |
| 0.2853 | 3.07 | 800 | 0.2970 | 14.3180 |
| 0.2416 | 3.84 | 1000 | 0.2874 | 14.4271 |
### Framework versions
- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2