roberta-finetuned-WebClassification-v2-smalllinguaENv2

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: 1.7384
• Accuracy: 0.55
• F1: 0.55
• Precision: 0.55
• Recall: 0.55

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	20	2.9187	0.075	0.075	0.075	0.075
No log	2.0	40	2.8030	0.15	0.15	0.15	0.15
No log	3.0	60	2.6273	0.325	0.325	0.325	0.325
No log	4.0	80	2.3371	0.45	0.45	0.45	0.45
No log	5.0	100	2.1233	0.425	0.425	0.425	0.425
No log	6.0	120	1.9737	0.525	0.525	0.525	0.525
No log	7.0	140	1.8962	0.475	0.4750	0.475	0.475
No log	8.0	160	1.8013	0.525	0.525	0.525	0.525
No log	9.0	180	1.7384	0.55	0.55	0.55	0.55
No log	10.0	200	1.7237	0.55	0.55	0.55	0.55

Framework versions

• Transformers 4.31.0.dev0
• Pytorch 2.0.0
• Datasets 2.1.0
• Tokenizers 0.13.3