tasinhoque/roberta-large-go-emotions-3

roberta-large-go-emotions-2

This model is a fine-tuned version of roberta-large on the go_emotions dataset. It achieves the following results on the test set (with a threshold of 0.15):

• Accuracy: 0.44020
• Precision: 0.5041
• Recall: 0.5461
• F1: 0.5180

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: 5e-05
• train_batch_size: 128
• eval_batch_size: 128
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 9

Training results

Training Loss	Epoch	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	0.0889	0.4043	0.4807	0.4568	0.4446
0.1062	2.0	0.0828	0.4113	0.4608	0.5363	0.4868
0.1062	3.0	0.0813	0.4201	0.5198	0.5612	0.5227
No log	4.0	0.0862	0.4292	0.5012	0.5558	0.5208
0.0597	5.0	0.0924	0.4329	0.5164	0.5362	0.5151
0.0597	6.0	0.0956	0.4445	0.5241	0.5328	0.5161
No log	7.0	0.0962	0.4648	0.5138	0.5277	0.5151
0.0458	8.0	0.0962	0.4462	0.5257	0.5270	0.5203
0.0458	9.0	0.1029	0.4432	0.5076	0.5249	0.5111

Framework versions

• Transformers 4.20.1
• Pytorch 1.12.0
• Datasets 2.1.0
• Tokenizers 0.12.1