results – AI Model by karangupta224 | AlphaNeural AI

You can deploy this model and start earning money today!

karangupta224/
results

like

0

text-classification

generated_from_trainer

mental/mental-roberta-base

autotrain_compatible

endpoints_compatible

Views

No views yet

results

This model is a fine-tuned version of mental/mental-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.7715
Accuracy: 0.8014
F1: 0.8161
Precision: 0.7816
Recall: 0.8537

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: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 8
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.3921	0.99	31	0.4379	0.8042	0.8153	0.7943	0.8374
0.3376	1.98	62	0.4358	0.8112	0.8173	0.8162	0.8184
0.3126	2.98	93	0.4642	0.7972	0.8172	0.7642	0.8780
0.2838	4.0	125	0.4438	0.8196	0.8264	0.8209	0.8320
0.2504	4.99	156	0.5249	0.7958	0.8161	0.7624	0.8780
0.2912	5.98	187	0.6067	0.7972	0.8221	0.7511	0.9079
0.1335	6.98	218	0.7014	0.8	0.8197	0.7665	0.8808
0.1579	7.94	248	0.7715	0.8014	0.8161	0.7816	0.8537

Framework versions

Transformers 4.39.1
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2