roberta_comp – AI Model by gustavecortal | AlphaNeural AI

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gustavecortal/
roberta_comp

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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roberta_comp

This model is a fine-tuned version of ibm/ColD-Fusion on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3066
F1: 0.8077
Roc Auc: 0.8650
Accuracy: 0.5765
Recall: 0.8105

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy	Recall
No log	1.0	231	0.3455	0.7594	0.8284	0.5306	0.7474
No log	2.0	462	0.2986	0.7986	0.8569	0.5714	0.7930
0.3143	3.0	693	0.3006	0.8056	0.8632	0.5867	0.8070
0.3143	4.0	924	0.3066	0.8077	0.8650	0.5765	0.8105
0.1365	5.0	1155	0.3117	0.8028	0.8618	0.5663	0.8070

Framework versions

Transformers 4.25.1
Pytorch 1.13.1+rocm5.2
Datasets 2.8.0
Tokenizers 0.13.2