BlocksmithV2

This model is a fine-tuned version of DesilDev/Blocksmith on the samsum dataset. It achieves the following results on the evaluation set:

• Loss: 1.8786
• Rouge1: 39.0411
• Rouge2: 16.2095
• Rougel: 32.6745
• Rougelsum: 35.9911
• Gen Len: 16.28

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
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.115	1.0	921	1.8786	39.0411	16.2095	32.6745	35.9911	16.28

Framework versions

• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1