bart-large-finetuned-aeslc – AI Model by sohamchougule | AlphaNeural AI

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sohamchougule/
bart-large-finetuned-aeslc

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bart-large-finetuned-aeslc

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

Loss: 4.6657
Rouge1: 38.0679
Rouge2: 19.8904
Rougel: 37.1179
Rougelsum: 37.1066
Gen Len: 9.1316

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: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.6268	1.0	7218	4.4738	36.0615	18.1082	35.2023	35.175	8.0694
1.9548	2.0	14436	4.4965	37.1784	19.2713	36.2803	36.2347	9.2699
1.4117	3.0	21654	4.6657	38.0679	19.8904	37.1179	37.1066	9.1316

Framework versions

Transformers 4.27.4
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3