Neuro_continuous – AI Model by ajrayman | AlphaNeural AI

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ajrayman/
Neuro_continuous

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text-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

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Neuro_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: 0.0252
Rmse: 0.1589
Mae: 0.1265
Corr: 0.4714

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	0.0268	0.1638	0.1331	0.4401
No log	2.0	470	0.0276	0.1661	0.1343	0.4571
0.0442	3.0	705	0.0244	0.1563	0.1243	0.4728
0.0442	4.0	940	0.0252	0.1587	0.1260	0.4711
0.024	5.0	1175	0.0252	0.1589	0.1265	0.4714

Framework versions

Transformers 4.44.1
Pytorch 1.11.0
Datasets 2.12.0
Tokenizers 0.19.1