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

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mnavas/
roberta-finetuned-WebClassification-v2-smalllinguaEN

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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roberta-finetuned-WebClassification-v2-smalllinguaEN

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: 1.5844
Accuracy: 0.7143
F1: 0.7143
Precision: 0.7143
Recall: 0.7143

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	7	2.3084	0.0714	0.0714	0.0714	0.0714
No log	2.0	14	2.2951	0.2857	0.2857	0.2857	0.2857
No log	3.0	21	2.2725	0.2143	0.2143	0.2143	0.2143
No log	4.0	28	2.0608	0.2143	0.2143	0.2143	0.2143
No log	5.0	35	1.8552	0.3571	0.3571	0.3571	0.3571
No log	6.0	42	1.6846	0.5714	0.5714	0.5714	0.5714
No log	7.0	49	1.5844	0.7143	0.7143	0.7143	0.7143
No log	8.0	56	1.4531	0.7143	0.7143	0.7143	0.7143
No log	9.0	63	1.3746	0.7143	0.7143	0.7143	0.7143
No log	10.0	70	1.3663	0.7143	0.7143	0.7143	0.7143

Framework versions

Transformers 4.27.3
Pytorch 2.0.0+cpu
Datasets 2.10.1
Tokenizers 0.13.2