Whisper Medium FLEURS Language Identification

This model is a fine-tuned version of openai/whisper-medium on the FLEURS subset of the google/xtreme_s dataset. It achieves the following results on the evaluation set:

• Loss: 0.8413
• Accuracy: 0.8805

To reproduce this run, execute the command in run.sh .

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: 3e-05
• train_batch_size: 16
• eval_batch_size: 32
• seed: 0
• 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_ratio: 0.1
• num_epochs: 3.0

Training results

Framework versions

• Transformers 4.27.0.dev0
• Pytorch 1.13.1
• Datasets 2.9.0
• Tokenizers 0.13.2