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t5-small-finetuned-news
Ftmhd/t5-small-finetuned-news
t5-small-finetuned-news is a machine learning model from Ftmhd. 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
- Oct 4, 2024
- Updated
- Nov 18, 2024
- SHA
- b7474d2f
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-news
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5749
- Rouge1: 43.7874
- Rouge2: 24.2639
- Rougel: 40.5888
- Rougelsum: 40.5008
- Gen Len: 18.6475
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: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 175 | 1.5966 | 42.795 | 23.6707 | 39.6859 | 39.6641 | 18.6115 |
| No log | 2.0 | 350 | 1.5749 | 43.7874 | 24.2639 | 40.5888 | 40.5008 | 18.6475 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Oct 4, 2024
- Updated
- Nov 18, 2024