google-electra-base-discriminator-english-sentweet-sentiment

This model is a fine-tuned version of google/electra-base-discriminator on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.5459
• Accuracy: 0.8194
• Precision: 0.8367
• Recall: 0.8273
• F1: 0.8189

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: 5e-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: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	81	0.4708	0.7847	0.8008	0.7924	0.7841
No log	2.0	162	0.4815	0.8090	0.8346	0.8185	0.8078
No log	3.0	243	0.4717	0.8160	0.8448	0.8260	0.8146
No log	4.0	324	0.4291	0.8229	0.8351	0.8296	0.8227
No log	5.0	405	0.4318	0.8090	0.8099	0.8113	0.8089
No log	6.0	486	0.5459	0.8194	0.8367	0.8273	0.8189

Framework versions

• Transformers 4.24.0
• Pytorch 1.13.1+cu117
• Datasets 2.6.1
• Tokenizers 0.11.0