long-t5-tglobal-base-sci-simplify-scisumm

This model is a fine-tuned version of pszemraj/long-t5-tglobal-base-sci-simplify on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.0275
• Rouge1: 44.684
• Rouge2: 22.6677
• Rougel: 33.7218
• Rougelsum: 41.5818
• Gen Len: 106.08

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: 4e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.01
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	0.99	28	1.0410	42.356	18.864	30.1792	39.0252	92.08
No log	1.97	56	1.0299	46.6047	23.6896	35.2928	43.5705	101.62
No log	2.96	84	1.0275	44.684	22.6677	33.7218	41.5818	106.08

Framework versions

• Transformers 4.38.1
• Pytorch 2.1.2
• Datasets 2.18.0
• Tokenizers 0.15.2