This model is a fine-tuned version of google/electra-small-discriminator on the tweet_eval dataset. It achieves the following results on the evaluation set:

Loss: 0.7133
Accuracy: 0.6944
Precision: 0.6975
Recall: 0.6944
Micro-avg-recall: 0.6944
Micro-avg-precision: 0.6944

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: 16
eval_batch_size: 16
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	Precision	Recall	Micro-avg-recall	Micro-avg-precision
0.633	1.0	2851	0.6916	0.6968	0.6972	0.6968	0.6968	0.6968
0.6322	2.0	5702	0.7180	0.6915	0.6948	0.6915	0.6915	0.6915
0.5729	3.0	8553	0.7133	0.6944	0.6975	0.6944	0.6944	0.6944

Framework versions

Transformers 4.33.0
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3

Priyanka-Balivada/electra-3-epoch-sentiment

electra-3-epoch-sentiment

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Priyanka-Balivada/
electra-3-epoch-sentiment