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

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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
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 43
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 5

Training results

Framework versions

• —Transformers 4.21.3
• —Pytorch 1.12.1+cu113
• —Datasets 2.4.0
• —Tokenizers 0.12.1