metadata

license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - google/fleurs
metrics:
  - wer
model-index:
  - name: Whisper_small_Occitan
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs
          type: google/fleurs
          config: oc_fr
          split: test
        metrics:
          - name: Wer
            type: wer
            value: 39.84848484848485

Whisper_small_Occitan

This model is a fine-tuned version of bofenghuang/whisper-small-cv11-french on the google/fleurs oc_fr dataset. It achieves the following results on the evaluation set:

Loss: 1.1744
Wer: 39.8485

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: 2000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0087	30.77	400	1.1744	39.8485
0.001	61.54	800	1.2807	39.8939
0.0005	92.31	1200	1.3227	40.3447
0.0004	123.08	1600	1.3445	40.1098
0.0003	153.85	2000	1.3524	40.0492

Framework versions

Transformers 4.25.1
Pytorch 1.13.0+cu117
Datasets 2.7.1
Tokenizers 0.13.2