This model is a fine-tuned version of roberta-large on the Twitter Sentiment Datasets dataset. It achieves the following results on the evaluation set:

Loss: 0.5990
Accuracy: 0.8117

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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
0.6504	1.0	1250	0.4964	0.7967
0.4385	2.0	2500	0.5048	0.8064
0.3285	3.0	3750	0.5458	0.8101
0.2272	4.0	5000	0.5990	0.8117
0.1596	5.0	6250	0.7201	0.8089

Framework versions

Transformers 4.46.3
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3

luluw/roberta-large-finetuned-sentiment

roberta-large-finetuned-sentiment

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

luluw/
roberta-large-finetuned-sentiment