ml_sum_v2 – AI Model by mHossain | AlphaNeural AI

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mHossain/
ml_sum_v2

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text2text-generation

generated_from_trainer

mHossain/ml_sum_v1

text-generation-inference

endpoints_compatible

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ml_sum_v2

This model is a fine-tuned version of mHossain/ml_sum_v1 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.9401
Rouge1: 8.1448
Rouge2: 3.3615
Rougel: 7.4641
Rougelsum: 7.9361
Gen Len: 19.0

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
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: 5000
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	312	2.1706	7.2919	2.8117	6.7418	7.1173	19.0
2.4911	2.0	625	2.1012	7.7986	3.0952	7.1505	7.5818	19.0
2.4911	3.0	937	2.0373	8.0535	3.2228	7.3877	7.8365	19.0
2.3572	4.0	1250	1.9865	8.1591	3.31	7.4577	7.9114	19.0
2.2455	4.99	1560	1.9401	8.1448	3.3615	7.4641	7.9361	19.0

Framework versions

Transformers 4.38.2
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2