Bart_reddit_tifu

This model is a fine-tuned version of facebook/bart-large on the reddit_tifu dataset. It achieves the following results on the evaluation set:

• Loss: 2.5035
• Rouge1: 0.2709
• Rouge2: 0.0948
• Rougel: 0.2244
• Rougelsum: 0.2244
• Gen Len: 19.3555
• Precision: 0.8768
• Recall: 0.8648
• F1: 0.8705

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: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• 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	Precision	Recall	F1
2.6968	1.0	2370	2.5385	0.2634	0.0907	0.218	0.2182	19.4438	0.8766	0.8641	0.8701
2.4746	2.0	4741	2.5077	0.273	0.0941	0.2238	0.2239	19.2572	0.8774	0.8655	0.8712
2.3066	3.0	7111	2.5012	0.2671	0.0936	0.221	0.2211	19.3071	0.8756	0.864	0.8696
2.2041	4.0	9480	2.5035	0.2709	0.0948	0.2244	0.2244	19.3555	0.8768	0.8648	0.8705

Framework versions

• Transformers 4.36.0
• Pytorch 2.0.1+cu117
• Datasets 2.14.5
• Tokenizers 0.15.0