Whisper Large V2 Bn

🚀 Whisper Large-v2 Bengali

This model is a fine - tuned version of openai/whisper-large-v2 on the Bengali dataset, aiming to provide high - quality automatic speech recognition for Bengali.

🚀 Quick Start

This model is a fine - tuned version of openai/whisper-large-v2 on the mozilla - foundation/common_voice_11_0 bn dataset. It achieves the following results on the evaluation set:

• Loss: 0.0746
• Wer: 11.1086

✨ Features

• Fine - Tuned: Based on the powerful openai/whisper-large-v2 model, fine - tuned on the Bengali dataset.
• Good Performance: Achieves a Wer of 11.1086 on the evaluation set.

📚 Documentation

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: 32
• eval_batch_size: 16
• seed: 42
• distributed_type: multi - GPU
• optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• training_steps: 1000

Training results

Framework versions

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

📄 License

This model is released under the Apache 2.0 license.

📦 Model Information