GraphCodebert-gpt2 – AI Model by abhi11nav | AlphaNeural AI

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abhi11nav/
GraphCodebert-gpt2

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encoder-decoder

text2text-generation

generated_from_trainer

endpoints_compatible

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GraphCodebert-gpt2

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

Loss: 3.6964
Rouge2 Precision: 0.1809
Rouge2 Recall: 0.1775
Rouge2 Fmeasure: 0.1747

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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 2000
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge2 Precision	Rouge2 Recall	Rouge2 Fmeasure
No log	0.29	500	5.0350	0.0889	0.0797	0.0819
6.0048	0.58	1000	4.4849	0.1159	0.116	0.1138
6.0048	0.87	1500	4.1607	0.151	0.1474	0.1452
4.2848	1.15	2000	4.0174	0.1558	0.1465	0.1471
4.2848	1.44	2500	3.8264	0.1786	0.1683	0.1685
3.8448	1.73	3000	3.6964	0.1809	0.1775	0.1747

Framework versions

Transformers 4.25.1
Pytorch 1.13.1+cu116
Datasets 2.8.0
Tokenizers 0.13.2