Task1a

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: 0.8168
• Accuracy: 0.8286

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	18	0.7392	0.3714
No log	2.0	36	0.5119	0.8
No log	3.0	54	0.5153	0.8
No log	4.0	72	0.6688	0.7714
No log	5.0	90	0.5781	0.8286
No log	6.0	108	0.7906	0.8286
No log	7.0	126	0.8076	0.8286
No log	8.0	144	0.8083	0.8286
No log	9.0	162	0.8150	0.8286
No log	10.0	180	0.8168	0.8286

Framework versions

• Transformers 4.27.4
• Pytorch 2.0.0+cu118
• Datasets 2.11.0
• Tokenizers 0.13.3