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

luluw/deberta-base-tweet-sentiment

deberta-base-tweet-sentiment

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

luluw/
deberta-base-tweet-sentiment