gpt-2-10000 – AI Model by Baljinnyam | AlphaNeural AI

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Baljinnyam/
gpt-2-10000

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token-classification

generated_from_trainer

autotrain_compatible

text-generation-inference

endpoints_compatible

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gpt-2-10000

This model is a fine-tuned version of gpt2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2551
Precision: 0.1523
Recall: 0.2608
F1: 0.1923
Accuracy: 0.9175

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: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.4502	1.0	477	0.3178	0.1351	0.2289	0.1699	0.8953
0.3283	2.0	954	0.3014	0.1227	0.2220	0.1581	0.8985
0.3016	3.0	1431	0.2768	0.1441	0.2379	0.1795	0.9077
0.2824	4.0	1908	0.2687	0.1442	0.2415	0.1806	0.9103
0.2686	5.0	2385	0.2697	0.1374	0.2383	0.1743	0.9086
0.2568	6.0	2862	0.2573	0.1450	0.2525	0.1842	0.9140
0.2472	7.0	3339	0.2534	0.1492	0.2574	0.1889	0.9166
0.2405	8.0	3816	0.2548	0.1413	0.2515	0.1809	0.9153
0.2345	9.0	4293	0.2545	0.1489	0.2564	0.1884	0.9163
0.2299	10.0	4770	0.2551	0.1523	0.2608	0.1923	0.9175

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3