odinsynth_encoder_decoder_native_hf_test

enoriega/odinsynth_encoder_decoder_native_hf_test

odinsynth_encoder_decoder_native_hf_test is a machine learning model from enoriega. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.

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

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At a glance

Library: transformers
License: apache-2.0
Model type: encoder-decoder
Access: Public
Created: Apr 11, 2023
Updated: Apr 11, 2023
SHA: 2b190199

Datasets

enoriega/odinsynth_sequence_dataset

Model card

From the Hugging Face model README

odinsynth_encoder_decoder_native_hf_test

This model is a fine-tuned version of bert-base-uncased on the enoriega/odinsynth_sequence_dataset synthetic_surface dataset. It achieves the following results on the evaluation set:

Loss: 0.0533
Accuracy: 0.9332

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: 3
eval_batch_size: 3
seed: 42
gradient_accumulation_steps: 200
total_train_batch_size: 600
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
6.5753	0.67	60	6.1666	0.0150
2.5262	1.34	120	2.1713	0.9345
0.2343	2.01	180	0.1787	0.9346
0.0713	2.68	240	0.0686	0.9330
0.0631	3.35	300	0.0621	0.9334
0.0603	4.02	360	0.0594	0.9332
0.0589	4.69	420	0.0583	0.9334
0.0579	5.36	480	0.0572	0.9336
0.0575	6.03	540	0.0566	0.9333
0.0561	6.69	600	0.0562	0.9333
0.0559	7.36	660	0.0559	0.9332
0.0551	8.03	720	0.0556	0.9332
0.0548	8.7	780	0.0552	0.9333
0.0546	9.37	840	0.0550	0.9333
0.0539	10.04	900	0.0547	0.9331
0.0546	10.71	960	0.0544	0.9332
0.0538	11.38	1020	0.0543	0.9335
0.0534	12.05	1080	0.0540	0.9333
0.0532	12.72	1140	0.0539	0.9334
0.0525	13.39	1200	0.0538	0.9334
0.0526	14.06	1260	0.0538	0.9331
0.0527	14.73	1320	0.0536	0.9331
0.0529	15.4	1380	0.0536	0.9331
0.0526	16.07	1440	0.0535	0.9331
0.0524	16.74	1500	0.0534	0.9333
0.0516	17.41	1560	0.0534	0.9331
0.0527	18.08	1620	0.0534	0.9332
0.0521	18.74	1680	0.0533	0.9332
0.0519	19.41	1740	0.0533	0.9332

Framework versions

Transformers 4.27.4
Pytorch 2.0.0
Datasets 2.11.0
Tokenizers 0.11.0

Library: transformers
Type: encoder-decoder
License: apache-2.0
Created: Apr 11, 2023
Updated: Apr 11, 2023