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

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sercetexam9/
roberta-large-finetuned-augmentation-LUNAR-TAPT-macro

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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-macro

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: 0.2832
F1: 0.8635
Roc Auc: 0.8937
Accuracy: 0.7150

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
0.2744	1.0	421	0.2710	0.7932	0.8326	0.5754
0.2287	2.0	842	0.2281	0.8454	0.8815	0.6758
0.1678	3.0	1263	0.2293	0.8563	0.8879	0.7049
0.1287	4.0	1684	0.2491	0.8619	0.8918	0.7126
0.1298	5.0	2105	0.2591	0.8633	0.8936	0.7173
0.0788	6.0	2526	0.2703	0.8612	0.8914	0.7138
0.0883	7.0	2947	0.2679	0.8605	0.8905	0.7203
0.0821	8.0	3368	0.2832	0.8635	0.8937	0.7150
0.0739	9.0	3789	0.2998	0.8601	0.8963	0.7156
0.0538	10.0	4210	0.2951	0.8615	0.8957	0.7167
0.0466	11.0	4631	0.2999	0.8626	0.8976	0.7126
0.0657	12.0	5052	0.3060	0.8608	0.8976	0.7203

Framework versions

Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0