finetuned_token_itr0_0.0002_webDiscourse_16_02_2022-21_00_50

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: 0.5530
• Precision: 0.0044
• Recall: 0.0182
• F1: 0.0071
• Accuracy: 0.7268

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: 0.0002
• 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	10	0.7051	0.0645	0.0323	0.0430	0.4465
No log	2.0	20	0.6928	0.0476	0.0161	0.0241	0.5546
No log	3.0	30	0.6875	0.0069	0.0484	0.0120	0.5533
No log	4.0	40	0.6966	0.0064	0.0323	0.0107	0.5832
No log	5.0	50	0.7093	0.0061	0.0323	0.0102	0.5742

Framework versions

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