2504separado1 – AI Model by adriansanz | AlphaNeural AI

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adriansanz/
2504separado1

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text-classification

generated_from_trainer

projecte-aina/roberta-base-ca-v2-cased-te

autotrain_compatible

endpoints_compatible

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2504v4-8ep

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

Loss: 0.5711
Accuracy: 0.8487
Precision: 0.8523
Recall: 0.8487
F1: 0.8484
Ratio: 0.5504

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: 8
seed: 42
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
num_epochs: 4
label_smoothing_factor: 0.1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Ratio
2.0709	0.9870	38	0.8049	0.7059	0.7073	0.7059	0.7054	0.4580
0.7325	2.0	77	0.6190	0.8067	0.8081	0.8067	0.8065	0.5336
0.6249	2.9870	115	0.5998	0.8109	0.8230	0.8109	0.8091	0.5966
0.5768	3.9481	152	0.5711	0.8487	0.8523	0.8487	0.8484	0.5504

Framework versions

Transformers 4.40.0
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1