|
|
--- |
|
|
language: |
|
|
- en |
|
|
license: apache-2.0 |
|
|
base_model: openai/whisper-small |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
datasets: |
|
|
- openai/whisper-small |
|
|
metrics: |
|
|
- wer |
|
|
model-index: |
|
|
- name: Whisper Small fine tuned with comms |
|
|
results: |
|
|
- task: |
|
|
name: Automatic Speech Recognition |
|
|
type: automatic-speech-recognition |
|
|
dataset: |
|
|
name: BrainHack ASR |
|
|
type: openai/whisper-small |
|
|
metrics: |
|
|
- name: Wer |
|
|
type: wer |
|
|
value: 0.004561529393675362 |
|
|
--- |
|
|
|
|
|
<!-- 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 fine tuned with comms |
|
|
|
|
|
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the BrainHack ASR dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.0818 |
|
|
- Wer: 0.0046 |
|
|
|
|
|
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- lr_scheduler_warmup_steps: 500 |
|
|
- training_steps: 5000 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|
|:-------------:|:-------:|:----:|:---------------:|:------:| |
|
|
| 0.0022 | 6.4935 | 1000 | 0.0641 | 0.0057 | |
|
|
| 0.0009 | 12.9870 | 2000 | 0.0705 | 0.0050 | |
|
|
| 0.0 | 19.4805 | 3000 | 0.0766 | 0.0045 | |
|
|
| 0.0 | 25.9740 | 4000 | 0.0805 | 0.0046 | |
|
|
| 0.0 | 32.4675 | 5000 | 0.0818 | 0.0046 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.40.2 |
|
|
- Pytorch 2.3.0+cu121 |
|
|
- Datasets 2.19.1 |
|
|
- Tokenizers 0.19.1 |
|
|
|
