finetuned-endpoints_classif_test-4_13_1246 – AI Model by fftristan | AlphaNeural AI

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fftristan/
finetuned-endpoints_classif_test-4_13_1246

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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finetuned-endpoints_classif_test-4_13_1246

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

Loss: 0.4666
F1: 0.8717
Accuracy: 0.8667
Precision: 0.9019
Recall: 0.8667

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: 10
eval_batch_size: 10
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 12
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy	Precision	Recall
2.0932	1.0	13	1.8419	0.3116	0.3667	0.3823	0.3667
1.683	2.0	26	1.5969	0.3338	0.4	0.4632	0.4
1.3516	3.0	39	1.3390	0.5505	0.5667	0.6117	0.5667
1.0476	4.0	52	1.0331	0.6773	0.7	0.7741	0.7
0.6697	5.0	65	0.8544	0.7635	0.7667	0.8483	0.7667
0.417	6.0	78	0.5855	0.8068	0.8	0.8722	0.8
0.2449	7.0	91	0.5300	0.8409	0.8333	0.89	0.8333
0.1387	8.0	104	0.5291	0.8717	0.8667	0.9019	0.8667
0.0898	9.0	117	0.4517	0.8717	0.8667	0.9019	0.8667
0.0605	10.0	130	0.4855	0.8717	0.8667	0.9019	0.8667
0.0474	11.0	143	0.4727	0.8717	0.8667	0.9019	0.8667
0.0436	12.0	156	0.4666	0.8717	0.8667	0.9019	0.8667

Framework versions

Transformers 4.28.0
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3