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t5-base-cnn
KalvinPhan/t5-base-cnn
t5-base-cnn is a machine learning model from KalvinPhan. 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 26, 2025
- Updated
- Oct 6, 2025
- SHA
- 15b1db9b
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. -->
t5-base-cnn
This model is a fine-tuned version of google-t5/t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 0.0
- Rouge2: 0.0
- Rougel: 0.0
- Rougelsum: 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 1.4159 | 0.0804 | 500 | 1.2113 | 26.8618 | 13.7400 | 22.6242 | 22.5895 |
| 1.3831 | 0.1608 | 1000 | 1.1629 | 27.1682 | 14.2922 | 22.9340 | 22.9407 |
| 1.4429 | 0.2412 | 1500 | 1.1740 | 26.3174 | 13.3691 | 22.1695 | 22.1162 |
| 1.449 | 0.3216 | 2000 | 1.1724 | 26.2449 | 13.2833 | 22.0983 | 22.0470 |
| 1.4263 | 0.4020 | 2500 | 1.1725 | 26.2259 | 13.2458 | 22.0971 | 22.0603 |
| 1.4482 | 0.4824 | 3000 | 1.1725 | 26.2291 | 13.2776 | 22.1100 | 22.0645 |
| 1.4241 | 0.5628 | 3500 | 1.1725 | 26.2545 | 13.2396 | 22.1039 | 22.0575 |
| 1.4162 | 0.6432 | 4000 | 1.1725 | 26.2714 | 13.2853 | 22.1341 | 22.1005 |
| 1.4222 | 0.7236 | 4500 | 1.1725 | 26.2655 | 13.2861 | 22.1245 | 22.0911 |
| 1.3981 | 0.8040 | 5000 | 1.1725 | 26.2334 | 13.2644 | 22.1037 | 22.0614 |
| 1.4436 | 0.8844 | 5500 | 1.1726 | 26.2563 | 13.2686 | 22.1135 | 22.0862 |
| 1.4375 | 0.9648 | 6000 | 1.1725 | 26.2445 | 13.2861 | 22.1145 | 22.0876 |
| 1.4218 | 1.0452 | 6500 | 1.1726 | 26.2385 | 13.2984 | 22.1388 | 22.1080 |
| 1.4205 | 1.1256 | 7000 | 1.1725 | 26.2472 | 13.2703 | 22.1307 | 22.0987 |
| 1.4015 | 1.2060 | 7500 | 1.1725 | 26.1918 | 13.2530 | 22.0918 | 22.0415 |
| 1.4307 | 1.2864 | 8000 | 1.1725 | 26.2286 | 13.2684 | 22.1133 | 22.0767 |
| 1.4436 | 1.3668 | 8500 | 1.1725 | 26.1782 | 13.2320 | 22.0806 | 22.0392 |
| 1.4147 | 1.4472 | 9000 | 1.1725 | 26.2300 | 13.2703 | 22.1014 | 22.0480 |
| 1.4059 | 1.5276 | 9500 | 1.1725 | 26.2352 | 13.2800 | 22.1248 | 22.0848 |
| 1.3891 | 1.608 | 10000 | 1.1725 | 26.2352 | 13.2800 | 22.1248 | 22.0848 |
| 0.0 | 1.6884 | 10500 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.0 | 1.7688 | 11000 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.0 | 1.8492 | 11500 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.0 | 1.9296 | 12000 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Sep 26, 2025
- Updated
- Oct 6, 2025