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

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IIIT-L/
albert-base-v2-finetuned-code-mixed-DS

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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albert-base-v2-finetuned-code-mixed-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: 1.0408
Accuracy: 0.7324
Precision: 0.6883
Recall: 0.6822
F1: 0.6833

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: 1.2766380106570283e-05
train_batch_size: 8
eval_batch_size: 8
seed: 43
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.9207	1.0	497	0.7810	0.6016	0.5878	0.5953	0.5264
0.7519	2.0	994	0.8159	0.6600	0.6020	0.6194	0.6015
0.6029	3.0	1491	0.8026	0.7163	0.6599	0.6604	0.6593
0.4259	4.0	1988	0.9464	0.7384	0.7058	0.6808	0.6822
0.2845	5.0	2485	1.0408	0.7324	0.6883	0.6822	0.6833

Framework versions

Transformers 4.21.3
Pytorch 1.12.1+cu113
Datasets 2.4.0
Tokenizers 0.12.1