metadata
language:
- br
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: openai/whisper-large-v2-breton
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: br
split: test
args: br
metrics:
- name: Wer
type: wer
value: 39.92705800625217
openai/whisper-large-v2-breton
This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7162
- Wer: 39.9271
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
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- 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: 50
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7423 | 0.1 | 100 | 0.8363 | 57.1553 |
| 0.4361 | 1.07 | 200 | 0.6833 | 46.7176 |
| 0.2227 | 2.03 | 300 | 0.6483 | 42.5929 |
| 0.1472 | 3.0 | 400 | 0.6511 | 42.4627 |
| 0.0892 | 3.1 | 500 | 0.6633 | 40.9604 |
| 0.0651 | 4.07 | 600 | 0.6807 | 39.7534 |
| 0.0416 | 5.04 | 700 | 0.6870 | 41.2383 |
| 0.0352 | 6.0 | 800 | 0.7315 | 39.9010 |
| 0.022 | 6.1 | 900 | 0.7201 | 40.4307 |
| 0.0195 | 7.07 | 1000 | 0.7162 | 39.9271 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2