roberta-large-finetuned-augmentation-LUNAR-TAPT-DAIR – AI Model by sercetexam9 | AlphaNeural AI

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roberta-large-finetuned-augmentation-LUNAR-TAPT-DAIR

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text-classification

generated_from_trainer

FacebookAI/roberta-large

autotrain_compatible

endpoints_compatible

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roberta-large-finetuned-augmentation-LUNAR-TAPT-DAIR

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

Loss: 0.3531
F1: 0.8753
Roc Auc: 0.9173
Accuracy: 0.7721

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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.2394	1.0	627	0.2378	0.7928	0.8559	0.6579
0.2141	2.0	1254	0.2185	0.8216	0.8747	0.6850
0.1336	3.0	1881	0.2149	0.8388	0.8913	0.7150
0.1087	4.0	2508	0.2141	0.8479	0.8978	0.7357
0.0701	5.0	3135	0.2390	0.8499	0.8992	0.7361
0.065	6.0	3762	0.2600	0.8483	0.9022	0.7377
0.0518	7.0	4389	0.2756	0.8593	0.9038	0.7425
0.0307	8.0	5016	0.2917	0.8598	0.9050	0.7497
0.0227	9.0	5643	0.3293	0.8559	0.9062	0.7433
0.0131	10.0	6270	0.3357	0.8598	0.9005	0.7577
0.0068	11.0	6897	0.3465	0.8654	0.9109	0.7569
0.0014	12.0	7524	0.3500	0.8711	0.9116	0.7641
0.0009	13.0	8151	0.3531	0.8753	0.9173	0.7721
0.0013	14.0	8778	0.3676	0.8718	0.9188	0.7681
0.0004	15.0	9405	0.3715	0.8748	0.9165	0.7725
0.0012	16.0	10032	0.3709	0.8745	0.9172	0.7737
0.0008	17.0	10659	0.3775	0.8734	0.9182	0.7717

Framework versions

Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0