This model is a fine-tuned version of bert-base-cased on the twitter-sentiment-analysis dataset. It achieves the following results on the evaluation set:

Loss: 0.6462
Accuracy: 0.8476

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: 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
0.4013	1.0	14999	0.3686	0.8394
0.3354	2.0	29998	0.4543	0.8493
0.2539	3.0	44997	0.6462	0.8476

Framework versions

Transformers 4.27.4
Pytorch 1.13.1+cu116
Datasets 2.11.0
Tokenizers 0.13.2

ghost0x07/bert-finetuned-sent-analysis

bert-finetuned-sent-analysis

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ghost0x07/
bert-finetuned-sent-analysis