<!-- 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. -->
tl_dr_summary_with_t5_base
This model is a fine-tuned version of t5-base on the tldr_news dataset. It achieves the following results on the evaluation set:
- Loss: 2.1219
- Rouge1: 0.4445
- Rouge2: 0.2515
- Rougel: 0.4146
- Rougelsum: 0.4153
- Gen Len: 13.9647
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: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 447 | 2.2145 | 0.4202 | 0.2384 | 0.3929 | 0.3928 | 13.8967 |
2.621 | 2.0 | 894 | 2.1558 | 0.4353 | 0.2428 | 0.4066 | 0.4066 | 13.738 |
2.3114 | 3.0 | 1341 | 2.1320 | 0.4425 | 0.2511 | 0.4132 | 0.4136 | 13.9307 |
2.2337 | 4.0 | 1788 | 2.1242 | 0.4455 | 0.2516 | 0.4157 | 0.4159 | 13.9345 |
2.1767 | 5.0 | 2235 | 2.1219 | 0.4445 | 0.2515 | 0.4146 | 0.4153 | 13.9647 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3