azmn-posicao – AI Model by belisards | AlphaNeural AI

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belisards/
azmn-posicao

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text-classification

generated_from_trainer

belisards/congretimbau

autotrain_compatible

endpoints_compatible

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

Loss: 0.5239
Accuracy: 0.8254
F1: 0.7442
Recall: 0.7267
Precision: 0.7727

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: 1e-05
train_batch_size: 32
eval_batch_size: 32
seed: 5151
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Recall	Precision
0.5681	1.0323	32	0.5508	0.75	0.4286	0.5	0.375
0.5233	2.0645	64	0.5138	0.7381	0.5146	0.5317	0.5897
0.4339	3.0968	96	0.4529	0.7917	0.6875	0.6706	0.7240
0.3907	4.1290	128	0.4087	0.8393	0.7683	0.75	0.7970
0.2166	5.1613	160	0.4054	0.8452	0.7867	0.7778	0.7976
0.14	6.1935	192	0.4474	0.8274	0.7716	0.7738	0.7696
0.0673	7.2258	224	0.5118	0.8393	0.7726	0.7579	0.7932

Framework versions

Transformers 4.45.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.20.1