t5-small-finetuned-summarizer
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9791
- Rouge1: 18.7536
- Rouge2: 9.301
- Rougel: 16.4984
- Rougelsum: 16.4631
- Gen Len: 20.0
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.0808 | 1.0 | 140 | 2.0266 | 19.8203 | 9.7737 | 16.9637 | 16.955 | 20.0 |
| 2.1085 | 2.0 | 280 | 2.0287 | 20.0127 | 10.2365 | 17.3745 | 17.399 | 20.0 |
| 2.0736 | 3.0 | 420 | 2.0214 | 19.1769 | 9.3315 | 16.6286 | 16.6305 | 20.0 |
| 2.0343 | 4.0 | 560 | 2.0003 | 19.1986 | 9.4173 | 16.9178 | 16.9076 | 20.0 |
| 2.0328 | 5.0 | 700 | 1.9958 | 19.8891 | 10.2545 | 16.9206 | 16.8979 | 20.0 |
| 1.9842 | 6.0 | 840 | 1.9895 | 19.0999 | 9.6965 | 16.3588 | 16.3508 | 20.0 |
| 1.9693 | 7.0 | 980 | 1.9793 | 19.3562 | 9.5736 | 16.3363 | 16.324 | 20.0 |
| 1.9574 | 8.0 | 1120 | 1.9826 | 18.705 | 9.0554 | 16.1865 | 16.1408 | 20.0 |
| 1.94 | 9.0 | 1260 | 1.9814 | 18.9642 | 9.1944 | 16.421 | 16.3972 | 20.0 |
| 1.9123 | 10.0 | 1400 | 1.9791 | 18.7536 | 9.301 | 16.4984 | 16.4631 | 20.0 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1