p1 – AI Model by adriansanz | AlphaNeural AI

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adriansanz/
p1

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text-classification

generated_from_trainer

zero-shot-classification

projecte-aina/roberta-base-ca-v2-cawikitc

autotrain_compatible

endpoints_compatible

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p1

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

Loss: 0.8254
Accuracy: 0.5
Precision: 0.25
Recall: 0.5
F1: 0.3333
Ratio: 1.0

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: 16
eval_batch_size: 2
seed: 47
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.06
lr_scheduler_warmup_steps: 4
num_epochs: 2
label_smoothing_factor: 0.1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Ratio
0.8263	0.38	10	0.8199	0.5	0.5	0.5	0.3473	0.0163
0.8283	0.75	20	0.8389	0.5	0.25	0.5	0.3333	1.0
0.8167	1.13	30	0.8325	0.5	0.25	0.5	0.3333	1.0
0.8183	1.51	40	0.8228	0.4973	0.2493	0.4973	0.3321	0.9973
0.8178	1.89	50	0.8254	0.5	0.25	0.5	0.3333	1.0

Framework versions

Transformers 4.38.2
Pytorch 2.1.0+cu121
Datasets 2.19.0
Tokenizers 0.15.2