correct_distilBERT_token_itr0_1e-05_all_01_03_2022-15_43_47

This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.3343
• Precision: 0.1651
• Recall: 0.3039
• F1: 0.2140
• Accuracy: 0.8493

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: 1e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• 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	Precision	Recall	F1	Accuracy
No log	1.0	30	0.4801	0.0352	0.0591	0.0441	0.7521
No log	2.0	60	0.3795	0.0355	0.0795	0.0491	0.8020
No log	3.0	90	0.3359	0.0591	0.1294	0.0812	0.8334
No log	4.0	120	0.3205	0.0785	0.1534	0.1039	0.8486
No log	5.0	150	0.3144	0.0853	0.1571	0.1105	0.8516

Framework versions

• Transformers 4.15.0
• Pytorch 1.10.1+cu113
• Datasets 1.18.0
• Tokenizers 0.10.3