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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: transcriber-t5-v8 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# transcriber-t5-v8 |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1924 |
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## Model description |
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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. |
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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. |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 20 |
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- eval_batch_size: 20 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.2215 | 0.23 | 500 | 0.2216 | |
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| 0.1814 | 0.47 | 1000 | 0.2197 | |
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| 0.2011 | 0.7 | 1500 | 0.2059 | |
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| 0.2595 | 0.94 | 2000 | 0.2009 | |
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| 0.2412 | 1.17 | 2500 | 0.2019 | |
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| 0.1785 | 1.41 | 3000 | 0.1970 | |
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| 0.1962 | 1.64 | 3500 | 0.1983 | |
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| 0.2009 | 1.88 | 4000 | 0.1963 | |
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| 0.2013 | 2.11 | 4500 | 0.1923 | |
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| 0.2715 | 2.35 | 5000 | 0.1929 | |
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| 0.2488 | 2.58 | 5500 | 0.1936 | |
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| 0.1185 | 2.81 | 6000 | 0.1924 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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