albert-base-v2-finetuned-TRAC-DS – AI Model by IIIT-L | AlphaNeural AI

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IIIT-L/
albert-base-v2-finetuned-TRAC-DS

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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albert-base-v2-finetuned-TRAC-DS

This model is a fine-tuned version of albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.8271
Accuracy: 0.6315
Precision: 0.6206
Recall: 0.6201
F1: 0.6147

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: 5.919508251872584e-05
train_batch_size: 16
eval_batch_size: 16
seed: 43
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.0373	1.0	612	1.1241	0.3627	0.5914	0.3618	0.2414
1.0617	2.0	1224	1.1039	0.3350	0.2781	0.3354	0.1740
0.9791	3.0	1836	0.8365	0.5989	0.6192	0.5887	0.5883
0.798	3.99	2448	0.8271	0.6315	0.6206	0.6201	0.6147

Framework versions

Transformers 4.21.3
Pytorch 1.12.1+cu113
Datasets 2.4.0
Tokenizers 0.12.1