|
--- |
|
language: |
|
- pt |
|
license: apache-2.0 |
|
tags: |
|
- whisper-event |
|
- generated_from_trainer |
|
datasets: |
|
- mozilla-foundation/common_voice_11_0 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Tiny PT |
|
results: |
|
- task: |
|
type: automatic-speech-recognition |
|
name: Automatic Speech Recognition |
|
dataset: |
|
name: Common Voice 11.0 |
|
type: mozilla-foundation/common_voice_11_0 |
|
config: pt |
|
split: test |
|
args: pt |
|
metrics: |
|
- type: wer |
|
value: 29.11 |
|
name: WER |
|
- task: |
|
type: automatic-speech-recognition |
|
name: Automatic Speech Recognition |
|
dataset: |
|
name: google/fleurs |
|
type: google/fleurs |
|
config: pt_br |
|
split: test |
|
metrics: |
|
- type: wer |
|
value: 26.36 |
|
name: WER |
|
- task: |
|
type: automatic-speech-recognition |
|
name: Automatic Speech Recognition |
|
dataset: |
|
name: mozilla-foundation/common_voice_9_0 |
|
type: mozilla-foundation/common_voice_9_0 |
|
config: pt |
|
split: test |
|
metrics: |
|
- type: wer |
|
value: 28.68 |
|
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 PT |
|
|
|
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on the Common Voice 11.0 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6077 |
|
- Wer: 29.9844 |
|
|
|
## 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: 64 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
| 0.4143 | 1.04 | 500 | 0.5325 | 32.7399 | |
|
| 0.2693 | 3.03 | 1000 | 0.4718 | 29.4867 | |
|
| 0.1724 | 5.01 | 1500 | 0.4758 | 28.7218 | |
|
| 0.0849 | 7.0 | 2000 | 0.5070 | 29.2211 | |
|
| 0.0659 | 8.04 | 2500 | 0.5223 | 29.3169 | |
|
| 0.0539 | 10.03 | 3000 | 0.5402 | 30.1458 | |
|
| 0.0376 | 12.02 | 3500 | 0.5755 | 29.9995 | |
|
| 0.0217 | 14.0 | 4000 | 0.6067 | 29.6565 | |
|
| 0.0168 | 15.04 | 4500 | 0.6082 | 29.8162 | |
|
| 0.0205 | 17.03 | 5000 | 0.6077 | 29.9844 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.0.dev0 |
|
- Pytorch 1.13.0+cu116 |
|
- Datasets 2.7.1.dev0 |
|
- Tokenizers 0.13.2 |
|
|
