finetuned_token_2e-05_all_16_02_2022-15_41_15

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: 0.1742
• Precision: 0.3447
• Recall: 0.3410
• F1: 0.3428
• Accuracy: 0.9455

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	0.3692	0.0868	0.2030	0.1216	0.8238
No log	2.0	76	0.3198	0.1674	0.3029	0.2157	0.8567
No log	3.0	114	0.3156	0.1520	0.3096	0.2039	0.8510
No log	4.0	152	0.3129	0.1753	0.3266	0.2281	0.8500
No log	5.0	190	0.3038	0.1716	0.3401	0.2281	0.8595

Framework versions

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