sentiment-model-saagie

This model is a fine-tuned version of prajjwal1/bert-tiny on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.5475
• Accuracy: 0.7933

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5168	1.0	1500	0.4738	0.7733
0.3809	2.0	3000	0.5253	0.7917
0.3372	3.0	4500	0.5475	0.7933

Framework versions

• Transformers 4.18.0
• Pytorch 1.8.1
• Datasets 2.12.0
• Tokenizers 0.12.1