DanSumT5-smallV_91332

This model is a fine-tuned version of Danish-summarisation/DanSumT5-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.6864
• Rouge1: 31.4187
• Rouge2: 8.4053
• Rougel: 18.0276
• Rougelsum: 28.7915
• Gen Len: 126.8529

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: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	0.97	29	2.7126	31.1174	7.9711	17.6697	28.3148	126.521
No log	1.95	58	2.6864	31.4187	8.4053	18.0276	28.7915	126.8529

Framework versions

• Transformers 4.30.2
• Pytorch 1.12.1+git7548e2f
• Datasets 2.13.2
• Tokenizers 0.13.3