FS_25_05 – AI Model by adriansanz | AlphaNeural AI

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adriansanz/
FS_25_05

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text-classification

generated_from_trainer

projecte-aina/roberta-base-ca-v2

autotrain_compatible

endpoints_compatible

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FS_25_05

This model is a fine-tuned version of projecte-aina/roberta-base-ca-v2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1403
Accuracy: 0.9745
Precision: 0.9751
Recall: 0.9743
F1: 0.9744
Ratio: 0.0529

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Ratio
1.7313	1.0	362	1.5891	0.9137	0.9237	0.9138	0.9148	0.0569
0.3284	2.0	724	0.2812	0.9529	0.9560	0.9528	0.9533	0.0490
0.103	3.0	1086	0.1580	0.9667	0.9681	0.9665	0.9663	0.0510
0.1073	4.0	1448	0.1532	0.9686	0.9693	0.9685	0.9686	0.0529
0.1295	5.0	1810	0.1403	0.9745	0.9751	0.9743	0.9744	0.0529

Framework versions

Transformers 4.40.2
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1