correct_distilBERT_token_itr0_1e-05_essays_01_03_2022-15_41_29

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: 0.3097
• Precision: 0.2769
• Recall: 0.4391
• F1: 0.3396
• Accuracy: 0.8878

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	11	0.4573	0.0094	0.0027	0.0042	0.7702
No log	2.0	22	0.3660	0.1706	0.3253	0.2239	0.8516
No log	3.0	33	0.3096	0.2339	0.408	0.2974	0.8827
No log	4.0	44	0.2868	0.2963	0.4693	0.3633	0.8928
No log	5.0	55	0.2798	0.3141	0.48	0.3797	0.8960

Framework versions

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