mT5-tfidf-10pass-all-questions-QA-22-06-2023-without-ams-with-nonfactual – AI Model by natope | AlphaNeural AI

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mT5-tfidf-10pass-all-questions-QA-22-06-2023-without-ams-with-nonfactual

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mT5-tfidf-10pass-all-questions-QA-22-06-2023-without-ams-with-nonfactual

This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.0171
Rouge1: 0.1497
Rouge2: 0.0386
Rougel: 0.1189
Rougelsum: 0.1189
Gen Len: 18.9316

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: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.6643	1.0	7356	2.0955	0.1434	0.0364	0.115	0.1148	18.7652
2.5667	2.0	14712	2.0301	0.1494	0.0387	0.1188	0.1187	18.9123
2.5061	3.0	22068	2.0171	0.1497	0.0386	0.1189	0.1189	18.9316

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3