Orderliness_continuous – AI Model by ajrayman | AlphaNeural AI

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ajrayman/
Orderliness_continuous

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text-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

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Orderliness_continuous

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

Loss: 0.0552
Rmse: 0.2349
Mae: 0.1906
Corr: 0.2473

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: 32
eval_batch_size: 32
seed: 1234
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.06
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Rmse	Mae	Corr
No log	1.0	235	0.0528	0.2299	0.1921	0.2641
No log	2.0	470	0.0489	0.2212	0.1798	0.2949
0.0745	3.0	705	0.0733	0.2707	0.2141	0.3079
0.0745	4.0	940	0.0478	0.2186	0.1811	0.2620
0.047	5.0	1175	0.0560	0.2365	0.1883	0.2743
0.047	6.0	1410	0.0552	0.2349	0.1906	0.2473

Framework versions

Transformers 4.44.1
Pytorch 1.11.0
Datasets 2.12.0
Tokenizers 0.19.1