t5-small-finetuned-summarizer
This model is a fine-tuned version of google-t5/t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7567
- Rouge1: 0.4206
- Rouge2: 0.1916
- Rougel: 0.3536
- Rougelsum: 0.354
- Gen Len: 16.6956
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.8732 | 1.0 | 921 | 1.7807 | 0.4159 | 0.1892 | 0.3488 | 0.349 | 16.6638 |
| 1.9217 | 2.0 | 1842 | 1.7619 | 0.4196 | 0.1908 | 0.3524 | 0.3528 | 16.7213 |
| 1.908 | 3.0 | 2763 | 1.7567 | 0.4206 | 0.1916 | 0.3536 | 0.354 | 16.6956 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for abhi227070/t5-small-finetuned-summarizer
Base model
google-t5/t5-small