mdeberta-v3-base-finetuned-french-green-stance – AI Model by mljn | AlphaNeural AI

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mljn/
mdeberta-v3-base-finetuned-french-green-stance

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text-classification

generated_from_trainer

microsoft/mdeberta-v3-base

autotrain_compatible

endpoints_compatible

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mdeberta-v3-base-finetuned-french-green-stance

This model is a fine-tuned version of microsoft/mdeberta-v3-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3085
Accuracy: 0.9533
F1 Macro: 0.9428
Accuracy Balanced: 0.9425
F1 Micro: 0.9533
Precision Macro: 0.9431
Recall Macro: 0.9425
Precision Micro: 0.9533
Recall Micro: 0.9533

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: 4
eval_batch_size: 4
seed: 42
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: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro	Accuracy Balanced	F1 Micro	Precision Macro	Recall Macro	Precision Micro	Recall Micro
0.3304	1.0	1393	0.4028	0.9160	0.8984	0.9035	0.9160	0.8937	0.9035	0.9160	0.9160
0.2085	2.0	2786	0.2895	0.9440	0.9298	0.9201	0.9440	0.9410	0.9201	0.9440	0.9440
0.1368	3.0	4179	0.3136	0.9519	0.9408	0.9384	0.9519	0.9432	0.9384	0.9519	0.9519
0.0374	4.0	5572	0.3085	0.9533	0.9428	0.9425	0.9533	0.9431	0.9425	0.9533	0.9533

Framework versions

Transformers 4.49.0
Pytorch 2.5.1+cu124
Datasets 3.3.2
Tokenizers 0.21.0