samsum_t5-base – AI Model by jialicheng | AlphaNeural AI

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jialicheng/
samsum_t5-base

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google/t5-v1_1-base

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samsum_42

This model is a fine-tuned version of google/t5-v1_1-base on the samsum dataset. It achieves the following results on the evaluation set:

Loss: 1.5075
Rouge1: 49.0229
Rouge2: 24.3221
Rougel: 40.7039
Rougelsum: 45.1477
Gen Len: 23.9792

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: 16
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	921	1.6420	44.8382	21.2515	37.1374	41.3685	22.9743
3.1861	2.0	1842	1.5848	47.24	23.0589	39.234	43.7105	23.9059
2.0725	3.0	2763	1.5335	48.2277	23.7578	40.0662	44.5023	24.4242
1.9171	4.0	3684	1.5174	48.4762	23.9941	40.2086	44.7825	23.8765
1.8449	5.0	4605	1.5075	49.0229	24.3221	40.7039	45.1477	23.9792

Framework versions

Transformers 4.39.3
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2