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t5-small-finetuned-2024-03-12
liamvbetts/t5-small-finetuned-2024-03-12
t5-small-finetuned-2024-03-12 is a machine learning model from liamvbetts. 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
- Apr 14, 2024
- Updated
- Apr 14, 2024
- SHA
- b45ffc05
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-small-finetuned-2024-03-12
This model is a fine-tuned version of ericjiliangli/t5-small-news-summarization on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7445
- Rouge1: 30.158
- Rouge2: 15.0234
- Rougel: 25.9885
- Rougelsum: 26.1101
- Gen Len: 18.759
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: 4e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.9214 | 1.0 | 328 | 1.7445 | 30.158 | 15.0234 | 25.9885 | 26.1101 | 18.759 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Library
- transformers
- Type
- t5
- Created
- Apr 14, 2024
- Updated
- Apr 14, 2024