deberta-base-tweet-sentiment

This model is a fine-tuned version of microsoft/deberta-base on the Twitter Sentiment Datasets dataset. It achieves the following results on the evaluation set:

• Loss: 0.4842
• Accuracy: 0.8019

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: 1.5e-05
• train_batch_size: 64
• eval_batch_size: 64
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 5
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.8569	0.9985	332	0.5507	0.7729
0.5439	2.0	665	0.5021	0.7947
0.4502	2.9985	997	0.4842	0.8019
0.3801	4.0	1330	0.5064	0.8013
0.3387	4.9925	1660	0.5141	0.8057

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.19.1