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knarasi1/
BART_pretrained_on_billsum_finetuned_on_small_SCOTUS_extracted_dataset

Name: BART_pretrained_on_billsum_finetuned_on_small_SCOTUS_extracted_dataset
Availability: InStock

generated_from_trainer

apache-2.0

endpoints_compatible

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BART_pretrained_on_billsum_finetuned_on_small_SCOTUS_extracted_dataset

This model is a fine-tuned version of bheshaj/bart-large-billsum-epochs20 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 3.6264
Rouge1: 0.1228
Rouge2: 0.0388
Rougel: 0.0995
Rougelsum: 0.1001
Gen Len: 19.1037

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	0.98	10	4.5839	0.107	0.0259	0.0896	0.0896	20.0
No log	1.98	20	4.2717	0.1329	0.0325	0.1086	0.1086	19.7378
No log	2.98	30	4.1413	0.1351	0.0333	0.1102	0.1105	19.7134
No log	3.98	40	4.0582	0.1406	0.0406	0.1151	0.115	19.5976
No log	4.98	50	3.9916	0.1418	0.0407	0.1144	0.1144	19.6829
No log	5.98	60	3.9373	0.1244	0.0356	0.1	0.1001	18.7134
No log	6.98	70	3.8867	0.1184	0.0322	0.0967	0.0972	18.4146
No log	7.98	80	3.8363	0.122	0.0325	0.0979	0.0981	18.4451
No log	8.98	90	3.7884	0.1183	0.0324	0.096	0.0967	18.8902
No log	9.98	100	3.7625	0.1153	0.0318	0.0939	0.094	18.8049
No log	10.98	110	3.7269	0.1063	0.0296	0.0882	0.0882	18.2378
No log	11.98	120	3.7023	0.1194	0.0314	0.0977	0.0981	19.1646
No log	12.98	130	3.6839	0.1275	0.0371	0.1053	0.105	19.5488
No log	13.98	140	3.6693	0.1237	0.0354	0.0998	0.1004	19.2561
No log	14.98	150	3.6578	0.1246	0.0371	0.1022	0.1023	19.1951
No log	15.98	160	3.6447	0.1299	0.0398	0.1062	0.1062	19.4329
No log	16.98	170	3.6366	0.1247	0.0355	0.1004	0.1007	19.1829
No log	17.98	180	3.6319	0.123	0.038	0.0994	0.1	19.0122
No log	18.98	190	3.6279	0.1225	0.0386	0.0994	0.1002	19.122
No log	19.98	200	3.6264	0.1228	0.0388	0.0995	0.1001	19.1037

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2

knarasi1/BART_pretrained_on_billsum_finetuned_on_small_SCOTUS_extracted_dataset

BART_pretrained_on_billsum_finetuned_on_small_SCOTUS_extracted_dataset

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

knarasi1/
BART_pretrained_on_billsum_finetuned_on_small_SCOTUS_extracted_dataset