idt5_base-silver-standard-lora

This model is a fine-tuned version of muchad/idt5-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 5.9463
• Rouge1: 0.1894
• Rouge2: 0.0
• Rougel: 0.1968
• Rougelsum: 0.1866

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: 0.0003
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
39.0609	1.0	149	7.6769	6.1515	0.1684	6.1419	6.1546
30.7822	2.0	298	6.1796	0.7179	0.0	0.7313	0.7174
28.7988	3.0	447	5.9463	0.1894	0.0	0.1968	0.1866

Framework versions

• PEFT 0.18.1
• Transformers 5.0.0
• Pytorch 2.10.0+cu128
• Datasets 4.8.3
• Tokenizers 0.22.2