transcriber-t5-v8

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

transcriber-t5-v8

This model is a fine-tuned version of odunola/transcriber-t5-v7 on the odunola/transcriberv3 dataset. It achieves the following results on the evaluation set:

• Loss: 0.1924

Model description

This model, a fine-tuned T5, is designed to pinpoint and extract specific Bible scriptures' chapter and verse from a string of text. It's a major component of a broader project but is also versatile enough for your other applications.

The model's learning is driven by a unique dataset, painstakingly compiled from transcripts of sermons on YouTube and various online platforms. This handpicked, curated data equips the model with a specialized understanding of religious discourse and biblical references.

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: 5e-05
• train_batch_size: 20
• eval_batch_size: 20
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 3

Training results

Framework versions

• Transformers 4.28.1
• Pytorch 2.0.0+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3