sentiment_test23feb

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: 0.5188
• Y True: [2 2 1 0 1 2 0 1 0 2 0 1 1 0 1 2 1 2 1 1 2 2 0 0 2 1 1 2 0 0 0 0 1 2 2 0 1 1 1 2 1 1 0 0 2 1 2 0 1 2 2 2 1 2 1 2 0 1 1 2 0 1 1 1 0 0 1 1 1 0 0 0 2 0 1 1 0 1 2 0 0 1 0 2 1 1 0 0 1 0 2 0 1 1 0 2 1 0 2 2 2 0 1 0 1 0 1 0 0 1 1 1 1 2 1 2 0 1 2 0 0 0 2 1 1 0 1 0 1 0 2 0 0 1 1 1 1 0 0 1 0 2 1 1 0 1 1 1 1 2 0 1 1 2 1 2 2 1 2 1 0 2 0 0 0 0 2 0 0 0 2 1 0 2 1 0 2 0 0 2 0 1 0 2 2 1 1 0 1 0 2 1 0 0 0 2 2 1 0 1 0 0 0 2 1 0 1 2 0 2 1 1 2 1 1 2 0 0 1 0 1 2 2 2 1 1 0 2 1 0]
• Y Pred: [0 1 1 0 1 2 0 2 0 1 0 1 2 0 1 1 1 1 1 1 2 1 0 0 1 1 1 2 0 0 0 0 1 0 2 0 1 1 1 2 1 1 1 0 2 1 1 0 1 2 2 2 1 0 1 2 0 1 1 2 0 1 2 1 0 0 1 1 1 0 0 0 2 0 1 1 2 1 2 0 0 0 0 2 1 1 0 0 1 0 2 0 1 1 0 2 1 0 1 2 0 0 1 0 1 0 1 0 0 1 2 2 1 2 1 2 0 1 2 0 0 0 0 2 0 0 1 0 1 0 1 0 0 1 1 1 1 0 0 1 0 1 1 1 0 2 1 1 1 2 0 1 1 2 1 2 1 1 2 1 0 2 0 0 0 0 2 0 0 0 1 1 0 2 1 2 0 0 0 2 0 1 2 2 2 1 1 0 1 2 0 1 0 0 0 0 2 1 0 1 0 0 0 0 1 0 1 1 0 2 1 1 2 1 1 1 0 0 1 0 1 0 1 0 1 1 0 2 1 2]
• Accuracy: 0.8217
• F1: 0.8146
• Precision: 0.8154
• Recall: 0.8217
• Confusion Matrix: [[76 1 5] [ 2 79 7] [11 15 34]]

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 50
• num_epochs: 5

Training results

Framework versions

• Transformers 4.26.1
• Pytorch 1.12.1+cu113
• Datasets 2.9.0
• Tokenizers 0.13.2