CS221-roberta-large-nrc-finetuned-augmentation – AI Model by sercetexam9 | AlphaNeural AI

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CS221-roberta-large-nrc-finetuned-augmentation

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text-classification

generated_from_trainer

FacebookAI/roberta-large

autotrain_compatible

endpoints_compatible

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CS221-roberta-large-nrc-finetuned-augmentation

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: 0.4713
F1: 0.6817
Roc Auc: 0.7787
Accuracy: 0.4866

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: 15

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.4185	1.0	215	0.4073	0.5570	0.7087	0.3524
0.3613	2.0	430	0.4023	0.6283	0.7459	0.3559
0.2661	3.0	645	0.3947	0.6200	0.7343	0.4061
0.2251	4.0	860	0.4144	0.6679	0.7708	0.4457
0.1618	5.0	1075	0.4270	0.6760	0.7715	0.4737
0.1138	6.0	1290	0.4713	0.6817	0.7787	0.4866
0.0785	7.0	1505	0.5387	0.6673	0.7711	0.4691
0.0785	8.0	1720	0.5692	0.6634	0.7615	0.4796
0.0622	9.0	1935	0.6067	0.6762	0.7727	0.4866
0.0549	10.0	2150	0.6334	0.6687	0.7683	0.4749
0.0357	11.0	2365	0.6719	0.6747	0.7726	0.4796
0.0216	12.0	2580	0.6841	0.6697	0.7677	0.4807
0.0259	13.0	2795	0.7054	0.6647	0.7655	0.4691
0.0221	14.0	3010	0.7068	0.6710	0.7690	0.4749
0.0316	15.0	3225	0.7083	0.6694	0.7677	0.4749

Framework versions

Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0