roberta-finetuned-WebClassification-v2-smalllinguaESv2 – AI Model by mnavas | AlphaNeural AI

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mnavas/
roberta-finetuned-WebClassification-v2-smalllinguaESv2

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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roberta-finetuned-WebClassification-v2-smalllinguaESv2

This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.3862
Accuracy: 0.6909
F1: 0.6909
Precision: 0.6909
Recall: 0.6909

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	1.0	28	2.9841	0.2	0.2000	0.2	0.2
No log	2.0	56	2.8109	0.1636	0.1636	0.1636	0.1636
No log	3.0	84	2.5334	0.3455	0.3455	0.3455	0.3455
No log	4.0	112	2.1164	0.5273	0.5273	0.5273	0.5273
No log	5.0	140	1.9152	0.5818	0.5818	0.5818	0.5818
No log	6.0	168	1.6678	0.6182	0.6182	0.6182	0.6182
No log	7.0	196	1.5647	0.6545	0.6545	0.6545	0.6545
No log	8.0	224	1.4473	0.6727	0.6727	0.6727	0.6727
No log	9.0	252	1.3862	0.6909	0.6909	0.6909	0.6909
No log	10.0	280	1.3647	0.6909	0.6909	0.6909	0.6909

Framework versions

Transformers 4.31.0.dev0
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3