jq_emo_distilbert – AI Model by tingtone | AlphaNeural AI

You can deploy this model and start earning money today!

tingtone/
jq_emo_distilbert

like

0

text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

jq_emo_distilbert

This model is a fine-tuned version of tingtone/jq_emo_distilbert on the emotion dataset. It achieves the following results on the evaluation set:

Loss: 0.3185
Accuracy: 0.9385

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: 1e-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
lr_scheduler_warmup_steps: 16000
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1042	1.0	1000	0.1816	0.932
0.0998	2.0	2000	0.1799	0.934
0.0957	3.0	3000	0.2015	0.935
0.0846	4.0	4000	0.2129	0.9335
0.0943	5.0	5000	0.2215	0.935
0.075	6.0	6000	0.2627	0.9375
0.0607	7.0	7000	0.2908	0.9345
0.0636	8.0	8000	0.3207	0.935
0.0953	9.0	9000	0.3165	0.936
0.0748	10.0	10000	0.3185	0.9385

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu117
Datasets 2.12.0
Tokenizers 0.13.3