llm_bn_sum

This model is a fine-tuned version of hishab/titulm-1b-bn-v1 on the crosssum dataset. It achieves the following results on the evaluation set:

• Loss: nan

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: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 2
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.0	1.0	2023	nan
0.0	2.0	4046	nan
0.0	3.0	6069	nan
0.0	4.0	8092	nan
0.0	5.0	10115	nan
0.0	6.0	12138	nan
0.0	7.0	14161	nan
0.0	8.0	16184	nan
0.0	9.0	18207	nan
0.0	10.0	20230	nan

Framework versions

• PEFT 0.10.0
• Transformers 4.38.2
• Pytorch 2.1.0+cu121
• Datasets 2.1.0
• Tokenizers 0.15.2