led_model

This model is a fine-tuned version of allenai/led-base-16384 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.4363
• Rouge1: 0.7117
• Rouge2: 0.5663
• Rougel: 0.684
• Rougelsum: 0.6843
• Gen Len: 15.7955

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
• 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: 4
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
0.6184	0.9995	546	0.4788	0.699	0.5474	0.6691	0.6694	15.7362
0.4523	1.9991	1092	0.4435	0.7029	0.5569	0.6773	0.6773	15.6763
0.3732	2.9986	1638	0.4392	0.7104	0.565	0.6826	0.6827	15.8442
0.3249	3.9982	2184	0.4363	0.7117	0.5663	0.684	0.6843	15.7955

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.0+cu121
• Datasets 3.0.0
• Tokenizers 0.19.1