mini_molformer_gsf – AI Model by victornica | AlphaNeural AI

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victornica/
mini_molformer_gsf

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text-generation

generated_from_trainer

autotrain_compatible

text-generation-inference

endpoints_compatible

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mini_molformer_gsf

This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6773

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: 0.0006
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 1000
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
1.8056	0.1	1000	1.0889
1.0277	0.19	2000	0.9550
0.9453	0.29	3000	0.9052
0.9026	0.39	4000	0.8735
0.8751	0.48	5000	0.8492
0.8538	0.58	6000	0.8306
0.8381	0.68	7000	0.8125
0.8225	0.77	8000	0.8030
0.8124	0.87	9000	0.7906
0.8	0.97	10000	0.7795
0.7895	1.07	11000	0.7724
0.78	1.16	12000	0.7617
0.7729	1.26	13000	0.7570
0.766	1.36	14000	0.7477
0.7577	1.45	15000	0.7425
0.7524	1.55	16000	0.7354
0.7454	1.65	17000	0.7286
0.739	1.74	18000	0.7220
0.7328	1.84	19000	0.7169
0.7276	1.94	20000	0.7095
0.7184	2.03	21000	0.7040
0.71	2.13	22000	0.6994
0.7064	2.23	23000	0.6948
0.7017	2.32	24000	0.6904
0.6982	2.42	25000	0.6866
0.6939	2.52	26000	0.6834
0.6909	2.61	27000	0.6811
0.6896	2.71	28000	0.6790
0.6881	2.81	29000	0.6778
0.6873	2.91	30000	0.6773

Framework versions

Transformers 4.30.2
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3