results – AI Model by TeamVioletEdifai | AlphaNeural AI

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TeamVioletEdifai/
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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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results

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

Loss: 1.0407
Accuracy: 0.563
F1: 0.5630
Precision: 0.5631
Recall: 0.563

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
1.0416	1.0	2500	1.0319	0.5479	0.5347	0.5392	0.5479
0.9488	2.0	5000	1.0248	0.5594	0.5535	0.5540	0.5594
0.8759	3.0	7500	1.0407	0.563	0.5630	0.5631	0.563
0.7576	4.0	10000	1.1242	0.5553	0.5539	0.5533	0.5553
0.6735	5.0	12500	1.2117	0.5528	0.5504	0.5500	0.5528
0.5951	6.0	15000	1.2677	0.5464	0.5442	0.5427	0.5464
0.5128	7.0	17500	1.4077	0.5401	0.5456	0.5570	0.5401
0.4343	8.0	20000	1.4986	0.5416	0.5433	0.5458	0.5416
0.3861	9.0	22500	1.5921	0.5402	0.5436	0.5497	0.5402
0.3713	10.0	25000	1.6282	0.5376	0.5401	0.5438	0.5376

Framework versions

Transformers 4.44.2
Pytorch 2.5.0+cu121
Datasets 3.1.0
Tokenizers 0.19.1