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t5-small-finetuned-xsum-apollo_adamw
guo1006/t5-small-finetuned-xsum-apollo_adamw
t5-small-finetuned-xsum-apollo_adamw is a machine learning model from guo1006. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- t5
- Access
- Public
- Created
- Sep 12, 2025
- Updated
- Sep 12, 2025
- SHA
- 8674f921
Base models
Datasets
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-small-finetuned-xsum-apollo_adamw
This model is a fine-tuned version of guo1006/t5-small-finetuned-xsum on the xsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.5163
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.APOLLO_ADAMW with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=proj=random,rank=1,scale=128.0,scale_type=tensor,update_proj_gap=300
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.8118 | 1.0 | 1500 | 2.5614 |
| 2.7674 | 2.0 | 3000 | 2.5336 |
| 2.753 | 3.0 | 4500 | 2.5197 |
| 2.7499 | 4.0 | 6000 | 2.5163 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2
- Library
- transformers
- Type
- t5
- Created
- Sep 12, 2025
- Updated
- Sep 12, 2025