finetuned_nli_classifier_deberta_v3_base_mnli_fever_anli_wanli_ling – AI Model by N1CKNGUYEN | AlphaNeural AI

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N1CKNGUYEN/
finetuned_nli_classifier_deberta_v3_base_mnli_fever_anli_wanli_ling

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text-classification

generated_from_trainer

N1CKNGUYEN/nli_classifier_deberta_v3_base_mnli_fever_anli_wanli_ling

autotrain_compatible

endpoints_compatible

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nli_classifier_finetuned

This model is a fine-tuned version of N1CKNGUYEN/nli_classifier on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5056
F1 Macro: 0.7970
F1 Micro: 0.8148
Accuracy Balanced: 0.7912
Accuracy: 0.8148
Precision Macro: 0.8056
Recall Macro: 0.7912
Precision Micro: 0.8148
Recall Micro: 0.8148

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: 128
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH 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: 0.06
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Macro	F1 Micro	Accuracy Balanced	Accuracy	Precision Macro	Recall Macro	Precision Micro	Recall Micro
No log	1.0	2	0.5685	0.7158	0.7407	0.7118	0.7407	0.7222	0.7118	0.7407	0.7407
No log	2.0	4	0.5056	0.7970	0.8148	0.7912	0.8148	0.8056	0.7912	0.8148	0.8148

Framework versions

Transformers 4.52.1
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1