File size: 2,422 Bytes
8300e57 3aadfd4 8300e57 7c882e1 8300e57 f88addf 8300e57 7c882e1 8300e57 7c882e1 8300e57 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 |
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: transcriber-t5-v8
results: []
---
<!-- 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](https://huggingface.co/odunola/transcriber-t5-v7) on the [odunola/transcriberv3](https://huggingface.co/datasets/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
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.2215 | 0.23 | 500 | 0.2216 |
| 0.1814 | 0.47 | 1000 | 0.2197 |
| 0.2011 | 0.7 | 1500 | 0.2059 |
| 0.2595 | 0.94 | 2000 | 0.2009 |
| 0.2412 | 1.17 | 2500 | 0.2019 |
| 0.1785 | 1.41 | 3000 | 0.1970 |
| 0.1962 | 1.64 | 3500 | 0.1983 |
| 0.2009 | 1.88 | 4000 | 0.1963 |
| 0.2013 | 2.11 | 4500 | 0.1923 |
| 0.2715 | 2.35 | 5000 | 0.1929 |
| 0.2488 | 2.58 | 5500 | 0.1936 |
| 0.1185 | 2.81 | 6000 | 0.1924 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
|