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samsum_model_t5_small_10_epochs
Jiraheya/samsum_model_t5_small_10_epochs
samsum_model_t5_small_10_epochs is a summarization model from Jiraheya. Use it when you need a shorter version of a longer text. 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
- Task
- Summarization
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Dec 6, 2024
- Updated
- Dec 6, 2024
- SHA
- d9e8e03b
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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_model_t5_small_10_epochs
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8701
- Rouge1: 0.4055
- Rouge2: 0.1762
- Rougel: 0.3372
- Rougelsum: 0.337
- Gen Len: 16.4738
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 200 | 1.9528 | 0.3844 | 0.1567 | 0.3184 | 0.3182 | 16.1362 |
| No log | 2.0 | 400 | 1.9221 | 0.3885 | 0.1613 | 0.3212 | 0.321 | 16.3325 |
| 2.0996 | 3.0 | 600 | 1.9072 | 0.3936 | 0.1661 | 0.3264 | 0.3259 | 16.2288 |
| 2.0996 | 4.0 | 800 | 1.8930 | 0.3984 | 0.1678 | 0.3295 | 0.3292 | 16.3375 |
| 2.0297 | 5.0 | 1000 | 1.8860 | 0.4005 | 0.1708 | 0.333 | 0.3329 | 16.355 |
| 2.0297 | 6.0 | 1200 | 1.8780 | 0.4023 | 0.1726 | 0.3341 | 0.3342 | 16.3375 |
| 2.0297 | 7.0 | 1400 | 1.8738 | 0.4025 | 0.1723 | 0.3347 | 0.3346 | 16.4275 |
| 1.9894 | 8.0 | 1600 | 1.8701 | 0.4064 | 0.1757 | 0.3369 | 0.3369 | 16.495 |
| 1.9894 | 9.0 | 1800 | 1.8706 | 0.4061 | 0.1767 | 0.3375 | 0.3375 | 16.4825 |
| 1.9735 | 10.0 | 2000 | 1.8701 | 0.4055 | 0.1762 | 0.3372 | 0.337 | 16.4738 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Summarization
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Dec 6, 2024
- Updated
- Dec 6, 2024