SumedhJoshi/idk

output

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

• Loss: 0.6705

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: 5e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Training results

TASK2_OversampledModel : precision recall f1-score support

       0       1.00      1.00      1.00      3230
       1       0.71      0.60      0.65      2037
       2       0.39      0.46      0.42      1195
       3       0.43      0.47      0.45      1074

accuracy                           0.73      7536

macro avg 0.63 0.63 0.63 7536 weighted avg 0.74 0.73 0.73 7536

Framework versions

• Transformers 4.39.3
• Pytorch 2.1.2
• Datasets 2.18.0
• Tokenizers 0.15.2