news-summarization-big-data – AI Model by dakshasinghal | AlphaNeural AI

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dakshasinghal/
news-summarization-big-data

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news-summarization-big-data

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

Loss: 2.3469

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: 2

Training results

Training Loss	Epoch	Step	Validation Loss
2.8084	0.18	500	2.5659
2.7712	0.36	1000	2.4634
2.7245	0.53	1500	2.4313
2.6138	0.71	2000	2.4270
2.6192	0.89	2500	2.3937
2.5076	1.07	3000	2.3851
2.5326	1.25	3500	2.3713
2.5412	1.42	4000	2.3658
2.4614	1.6	4500	2.3577
2.505	1.78	5000	2.3526
2.4364	1.96	5500	2.3469

Framework versions

Transformers 4.27.2
Pytorch 1.13.1+cu117
Datasets 2.11.0
Tokenizers 0.13.3