xsum_aligned_smallT5_full

This model is a fine-tuned version of google-t5/t5-small on the lilferrit/xsum_t5_distillation dataset. It achieves the following results on the evaluation set:

• Loss: 2.4093
• Rouge1: 22.8498
• Rouge2: 4.7818
• Rougel: 17.2861
• Rougelsum: 18.0665
• Gen Len: 33.6366

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: 0.0002
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Adafactor
• lr_scheduler_type: constant
• training_steps: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	0.0	5	2.6444	22.3341	4.3395	16.2507	17.8303	46.2437
No log	0.0	10	2.4093	22.8498	4.7818	17.2861	18.0665	33.6366

Framework versions

• Transformers 4.39.3
• Pytorch 2.2.2+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2