continue_pretrain_t5_base_more_tokens

This model is a fine-tuned version of google-t5/t5-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 4.9713
• Rouge: {'rouge1': 0.1482362658062074, 'rouge2': 0.13930032282405375, 'rougeL': 0.14788192707063608, 'rougeLsum': 0.14808345907939782}
• Exact Match: {'exact_match': 0.0}

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: 14
• eval_batch_size: 14
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 28
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge	Exact Match
0.1018	1.0	1786	4.8212	{'rouge1': 0.08214263320457528, 'rouge2': 0.07664435994602323, 'rougeL': 0.08165082402731275, 'rougeLsum': 0.08195136874817986}	{'exact_match': 0.0007692307692307692}
0.0492	2.0	3572	4.9667	{'rouge1': 0.14646008210615485, 'rouge2': 0.13764314957947393, 'rougeL': 0.14609763499439285, 'rougeLsum': 0.1462918679871027}	{'exact_match': 0.0}
0.0495	3.0	5358	4.9713	{'rouge1': 0.1482362658062074, 'rouge2': 0.13930032282405375, 'rougeL': 0.14788192707063608, 'rougeLsum': 0.14808345907939782}	{'exact_match': 0.0}

Framework versions

• Transformers 4.44.2
• Pytorch 2.1.2+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1