metadata
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper small Luxembourgish
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: google/fleurs lb_lu
type: google/fleurs
config: lb_lu
split: test
metrics:
- name: Wer
type: wer
value: 39.49904580152672
Whisper small Luxembourgish
This model is a fine-tuned version of bofenghuang/whisper-small-cv11-german-punct on the google/fleurs lb_lu dataset. It achieves the following results on the evaluation set:
- Loss: 1.1857
- Wer: 39.4990
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: 8
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- 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 |
|---|---|---|---|---|
| 0.0618 | 38.46 | 500 | 1.0104 | 43.2968 |
| 0.0055 | 76.92 | 1000 | 1.0684 | 40.1288 |
| 0.0024 | 115.38 | 1500 | 1.1056 | 40.9447 |
| 0.0014 | 153.85 | 2000 | 1.1280 | 39.7615 |
| 0.0013 | 192.31 | 2500 | 1.1415 | 39.9857 |
| 0.0008 | 230.77 | 3000 | 1.1573 | 39.7996 |
| 0.0006 | 269.23 | 3500 | 1.1682 | 40.0095 |
| 0.0006 | 307.69 | 4000 | 1.1769 | 39.7233 |
| 0.0005 | 346.15 | 4500 | 1.1826 | 39.5134 |
| 0.0004 | 384.62 | 5000 | 1.1857 | 39.4990 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2