t5-small-finetuned-cnn-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: 2.2247
- Rouge1: 24.0545
- Rouge2: 9.1969
- Rougel: 19.6469
- Rougelsum: 22.1421
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: 0.00056
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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 |
|---|---|---|---|---|---|---|---|
| 2.082 | 1.0 | 718 | 2.1358 | 23.8021 | 9.0803 | 19.6319 | 22.0566 |
| 1.8509 | 2.0 | 1436 | 2.1768 | 24.3438 | 9.8133 | 20.1128 | 22.2535 |
| 1.6881 | 3.0 | 2154 | 2.1883 | 24.4024 | 9.3123 | 20.1964 | 22.642 |
| 1.569 | 4.0 | 2872 | 2.2127 | 24.4912 | 9.8559 | 20.5182 | 22.7666 |
| 1.4801 | 5.0 | 3590 | 2.2247 | 24.0545 | 9.1969 | 19.6469 | 22.1421 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
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Model tree for Deepanshu7284/t5-small-finetuned-cnn-news
Base model
google-t5/t5-small