team1-roberta-bestrun – AI Model by Richard-Sieg-TH-Koln | AlphaNeural AI

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Richard-Sieg-TH-Koln/
team1-roberta-bestrun

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text-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

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roberta-base-finetuned

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

Loss: 0.2253
F1: 0.9351
Precision: 0.9356
Recall: 0.935

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: 5e-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
lr_scheduler_warmup_steps: 500
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Precision	Recall
0.426	1.0	1250	0.2329	0.9206	0.9218	0.92
0.6112	2.0	2500	0.3298	0.9212	0.9293	0.92
0.2796	3.0	3750	0.2613	0.9248	0.9267	0.926
0.0908	4.0	5000	0.1831	0.9419	0.9431	0.942
0.101	5.0	6250	0.2253	0.9351	0.9356	0.935

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu121
Datasets 2.14.6
Tokenizers 0.14.1