LongT5-Base-NSPCC – AI Model by scott156 | AlphaNeural AI

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scott156/
LongT5-Base-NSPCC

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text2text-generation

generated_from_trainer

google/long-t5-tglobal-base

endpoints_compatible

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LongT5-Base-NSPCC

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

Loss: 0.7756
Rouge1: 0.5243
Rouge2: 0.242
Rougel: 0.3113
Rougelsum: 0.3122
Gen Len: 331.8511

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: 0.0003
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.03
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
4.0417	0.9947	94	0.8455	0.4707	0.1986	0.2704	0.2718	303.4468
1.0117	2.0	189	0.8058	0.5178	0.239	0.3066	0.3077	326.3085
0.886	2.9947	283	0.7798	0.5085	0.2272	0.298	0.2989	348.7979
0.805	4.0	378	0.7725	0.5194	0.2386	0.309	0.31	331.3191
0.7724	4.9947	472	0.7749	0.5224	0.2423	0.3133	0.3147	333.6489
0.7514	5.9683	564	0.7756	0.5243	0.242	0.3113	0.3122	331.8511

Framework versions

Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1