gpt2-vietnamese

antphb/gpt2-vietnamese

gpt2-vietnamese is a text generation model from antphb. Use it when you need the model to write or continue text. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Generation
Library: transformers
Model type: gpt2
Access: Public
Created: Jun 17, 2023
Updated: Jun 18, 2023
SHA: cc509422

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Spaces

TanTran123/ai-thuong-hieu-ca-nhan

Model card

From the Hugging Face model README

gpt2-vietnamese

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

Loss: 2.7042

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 2000
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.03	500	3.5209
3.5302	0.06	1000	3.3902
3.5302	0.09	1500	3.2947
3.2733	0.12	2000	3.2116
3.2733	0.15	2500	3.1511
3.1431	0.18	3000	3.1054
3.1431	0.2	3500	3.0684
3.0471	0.23	4000	3.0372
3.0471	0.26	4500	3.0103
2.9957	0.29	5000	2.9863
2.9957	0.32	5500	2.9652
2.9472	0.35	6000	2.9452
2.9472	0.38	6500	2.9281
2.9164	0.41	7000	2.9123
2.9164	0.44	7500	2.8982
2.8991	0.47	8000	2.8856
2.8991	0.5	8500	2.8732
2.8672	0.53	9000	2.8621
2.8672	0.56	9500	2.8507
2.8456	0.59	10000	2.8411
2.8456	0.61	10500	2.8318
2.8074	0.64	11000	2.8234
2.8074	0.67	11500	2.8151
2.7959	0.7	12000	2.8077
2.7959	0.73	12500	2.8006
2.7918	0.76	13000	2.7943
2.7918	0.79	13500	2.7876
2.7773	0.82	14000	2.7818
2.7773	0.85	14500	2.7760
2.7648	0.88	15000	2.7706
2.7648	0.91	15500	2.7656
2.7559	0.94	16000	2.7611
2.7559	0.97	16500	2.7561
2.7461	1.0	17000	2.7521
2.7461	1.02	17500	2.7493
2.696	1.05	18000	2.7454
2.696	1.08	18500	2.7419
2.6808	1.11	19000	2.7390
2.6808	1.14	19500	2.7362
2.6803	1.17	20000	2.7335
2.6803	1.2	20500	2.7304
2.6753	1.23	21000	2.7278
2.6753	1.26	21500	2.7251
2.6732	1.29	22000	2.7228
2.6732	1.32	22500	2.7205
2.6687	1.35	23000	2.7189
2.6687	1.38	23500	2.7170
2.6667	1.41	24000	2.7154
2.6667	1.43	24500	2.7138
2.655	1.46	25000	2.7125
2.655	1.49	25500	2.7113
2.6592	1.52	26000	2.7100
2.6592	1.55	26500	2.7091
2.6435	1.58	27000	2.7084
2.6435	1.61	27500	2.7076
2.6577	1.64	28000	2.7071
2.6577	1.67	28500	2.7063
2.6487	1.7	29000	2.7060
2.6487	1.73	29500	2.7054
2.6596	1.76	30000	2.7052
2.6596	1.79	30500	2.7049
2.6513	1.82	31000	2.7046
2.6513	1.84	31500	2.7046
2.6564	1.87	32000	2.7044
2.6564	1.9	32500	2.7043
2.6532	1.93	33000	2.7043
2.6532	1.96	33500	2.7042
2.6582	1.99	34000	2.7042

Framework versions

Transformers 4.30.1
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3

Task: Text Generation
Library: transformers
Type: gpt2
Created: Jun 17, 2023
Updated: Jun 18, 2023