roberta-best-finetuned-hopes-fears – AI Model by jamiehudson | AlphaNeural AI

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jamiehudson/
roberta-best-finetuned-hopes-fears

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text-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

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roberta-best-finetuned-hopes-fears

This model is a fine-tuned version of FacebookAI/roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3593
Accuracy: 0.9434
F1 Weighted: 0.9453
Precision Fears: 0.7053
Recall Fears: 0.8171
F1 Fears: 0.7571
Precision Hopes: 0.7458
Recall Hopes: 0.88
F1 Hopes: 0.8073
Precision Neither: 0.9795
Recall Neither: 0.9579
F1 Neither: 0.9685

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: 1e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 600
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Weighted	Precision Fears	Recall Fears	F1 Fears	Precision Hopes	Recall Hopes	F1 Hopes	Precision Neither	Recall Neither	F1 Neither
No log	1.0	214	0.7739	0.8930	0.8651	0.4776	0.2602	0.3368	0.0	0.0	0.0	0.9129	0.9876	0.9488
0.8895	2.0	428	0.2800	0.8960	0.9087	0.4736	0.9106	0.6231	0.7417	0.89	0.8091	0.9893	0.8949	0.9397
0.2905	3.0	642	0.3252	0.9492	0.9496	0.7879	0.7398	0.7631	0.7143	0.95	0.8155	0.9759	0.9691	0.9725
0.2905	4.0	856	0.2671	0.9281	0.9340	0.5813	0.8862	0.7021	0.8018	0.89	0.8436	0.9869	0.9335	0.9595
0.1741	5.0	1070	0.3593	0.9434	0.9453	0.7053	0.8171	0.7571	0.7458	0.88	0.8073	0.9795	0.9579	0.9685

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1