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samsum_t5-xl
jialicheng/samsum_t5-xl
samsum_t5-xl is a machine learning model from jialicheng. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Aug 27, 2025
- Updated
- Aug 27, 2025
- SHA
- b9b4497e
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. -->
samsum_42
This model is a fine-tuned version of google/t5-v1_1-xl on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.1251
- Rouge1: 54.9849
- Rouge2: 30.5117
- Rougel: 45.8377
- Rougelsum: 50.8325
- Gen Len: 26.2286
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: 16
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 230 | 1.2376 | 51.063 | 26.1483 | 42.2509 | 47.1434 | 25.0954 |
| No log | 2.0 | 460 | 1.1684 | 53.4831 | 28.8893 | 44.3189 | 49.612 | 27.4010 |
| No log | 3.0 | 690 | 1.1291 | 54.4367 | 29.8842 | 45.5296 | 50.4519 | 26.2103 |
| No log | 4.0 | 921 | 1.1242 | 54.71 | 30.5588 | 45.4993 | 50.735 | 26.8154 |
| 1.5611 | 4.99 | 1150 | 1.1251 | 54.9849 | 30.5117 | 45.8377 | 50.8325 | 26.2286 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2
- Type
- t5
- License
- apache-2.0
- Created
- Aug 27, 2025
- Updated
- Aug 27, 2025