roberta-base-pr_tqacd – AI Model by rendchevi | AlphaNeural AI

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rendchevi/
roberta-base-pr_tqacd

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text-classification

generated_from_trainer

FacebookAI/roberta-base

text-embeddings-inference

endpoints_compatible

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roberta-base-pr_tqacd

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

Loss: 1.6056
F1 Macro: 0.5289
Precision: 0.5397
Recall: 0.5373
Accuracy: 0.7180

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: 32
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Macro	Precision	Recall	Accuracy
No log	1.0	354	1.8365	0.3820	0.4312	0.4000	0.6106
2.2658	2.0	708	1.3285	0.5013	0.5037	0.5722	0.6554
1.5226	3.0	1062	1.2491	0.5450	0.5421	0.6006	0.7090
1.5226	4.0	1416	1.3314	0.5476	0.5555	0.5767	0.7180
1.1009	5.0	1770	1.4114	0.5468	0.5457	0.5754	0.7203
0.7195	6.0	2124	1.6056	0.5289	0.5397	0.5373	0.7180

Framework versions

Transformers 4.57.1
Pytorch 2.8.0+cu128
Datasets 4.4.1
Tokenizers 0.22.1