BART1 – AI Model by MarPla | AlphaNeural AI

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MarPla/
BART1

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text2text-generation

generated_from_trainer

facebook/bart-large-cnn

endpoints_compatible

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BART1

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

Loss: 3.8706
Rouge1: 57.2472
Rouge2: 23.1787
Rougel: 41.8726
Rougelsum: 53.8183
Gen Len: 234.4232

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: 5e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
5.8303	0.0835	100	5.6762	48.0404	16.526	33.0315	45.2714	234.4232
5.2419	0.1671	200	5.1330	49.5121	17.8978	34.5708	46.291	234.4232
5.0085	0.2506	300	4.8037	52.3507	19.2179	36.3445	48.7473	234.4232
4.676	0.3342	400	4.5745	51.4939	19.2534	37.2441	48.7288	234.4232
4.4521	0.4177	500	4.4154	52.9389	20.2028	38.4139	49.9981	234.4232
4.4572	0.5013	600	4.2389	54.6029	21.0796	39.2355	51.1397	234.4232
4.2836	0.5848	700	4.1267	55.5174	22.1184	40.2744	52.0886	234.4232
4.2862	0.6684	800	4.0549	56.305	22.433	40.8636	52.6987	234.4232
4.0806	0.7519	900	3.9673	57.3033	22.873	41.2543	53.5936	234.4232
4.0806	0.8355	1000	3.9154	56.3519	22.7588	41.4512	52.9385	234.4232
3.8885	0.9190	1100	3.8706	57.2472	23.1787	41.8726	53.8183	234.4232

Framework versions

Transformers 4.41.2
Pytorch 2.3.1+cu121
Datasets 2.19.2
Tokenizers 0.19.1