finetuned_token_2e-05_16_02_2022-01_30_30

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: 0.1748
• Precision: 0.3384
• Recall: 0.3492
• F1: 0.3437
• Accuracy: 0.9442

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: 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	38	0.3180	0.0985	0.1648	0.1233	0.8643
No log	2.0	76	0.2667	0.1962	0.2698	0.2272	0.8926
No log	3.0	114	0.2374	0.2268	0.3005	0.2585	0.9062
No log	4.0	152	0.2305	0.2248	0.3247	0.2657	0.9099
No log	5.0	190	0.2289	0.2322	0.3166	0.2679	0.9102

Framework versions

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