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continue_pretrain_t5_base_more_tokens
VirgiF/continue_pretrain_t5_base_more_tokens
continue_pretrain_t5_base_more_tokens is a machine learning model from VirgiF. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Sep 16, 2024
- Updated
- Sep 16, 2024
- SHA
- 67210f32
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
continue_pretrain_t5_base_more_tokens
This model is a fine-tuned version of google-t5/t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.9713
- Rouge: {'rouge1': 0.1482362658062074, 'rouge2': 0.13930032282405375, 'rougeL': 0.14788192707063608, 'rougeLsum': 0.14808345907939782}
- Exact Match: {'exact_match': 0.0}
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: 2e-05
- train_batch_size: 14
- eval_batch_size: 14
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 28
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge | Exact Match |
|---|---|---|---|---|---|
| 0.1018 | 1.0 | 1786 | 4.8212 | {'rouge1': 0.08214263320457528, 'rouge2': 0.07664435994602323, 'rougeL': 0.08165082402731275, 'rougeLsum': 0.08195136874817986} | {'exact_match': 0.0007692307692307692} |
| 0.0492 | 2.0 | 3572 | 4.9667 | {'rouge1': 0.14646008210615485, 'rouge2': 0.13764314957947393, 'rougeL': 0.14609763499439285, 'rougeLsum': 0.1462918679871027} | {'exact_match': 0.0} |
| 0.0495 | 3.0 | 5358 | 4.9713 | {'rouge1': 0.1482362658062074, 'rouge2': 0.13930032282405375, 'rougeL': 0.14788192707063608, 'rougeLsum': 0.14808345907939782} | {'exact_match': 0.0} |
Framework versions
- Transformers 4.44.2
- Pytorch 2.1.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Sep 16, 2024
- Updated
- Sep 16, 2024