metadata

license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - facebook/multilingual_librispeech
metrics:
  - wer
model-index:
  - name: Whisper largeV2 Italian MLS
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: facebook/multilingual_librispeech italian
          type: facebook/multilingual_librispeech
          config: italian
          split: test
          args: italian
        metrics:
          - name: Wer
            type: wer
            value: 8.335297167365791

Whisper largeV2 Italian MLS

This model is a fine-tuned version of openai/whisper-large-v2 on the facebook/multilingual_librispeech italian dataset. It achieves the following results on the evaluation set:

Loss: 0.2051
Wer: 8.3353

Model description

The model is fine-tuned for 4000 updates/steps on multilingual librispeech Italian train data.

Zero-shot - 13.8 (MLS Italian test)
Fine-tune MLS Italian train - 8.33 (MLS Italian test) (-40%)

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: 32
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_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: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1115	1.02	1000	0.2116	9.4217
0.0867	2.03	2000	0.1964	9.7823
0.0447	3.05	3000	0.2001	9.6409
0.0426	4.07	4000	0.2051	8.3353

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.0+cu117
Datasets 2.7.1.dev0
Tokenizers 0.13.2