emotion_classification_2_continue

This model is a fine-tuned version of raffel-22/emotion_classification_2 on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.8978
• Accuracy: 0.725

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: 4e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	20	0.9714	0.7063
No log	2.0	40	0.9432	0.7188
No log	3.0	60	0.9633	0.7
No log	4.0	80	0.9322	0.7375
No log	5.0	100	0.8530	0.7063
No log	6.0	120	0.9063	0.7063
No log	7.0	140	0.8451	0.7125
No log	8.0	160	0.9672	0.6375
No log	9.0	180	0.9036	0.6937
No log	10.0	200	0.9261	0.6562
No log	11.0	220	0.8963	0.6937
No log	12.0	240	0.8852	0.7188
No log	13.0	260	0.8728	0.7063
No log	14.0	280	0.9559	0.6875
No log	15.0	300	0.9352	0.65
No log	16.0	320	0.8638	0.7
No log	17.0	340	0.9156	0.7
No log	18.0	360	1.0299	0.6687
No log	19.0	380	0.8983	0.675
No log	20.0	400	0.8858	0.7063
No log	21.0	420	0.9699	0.6937
No log	22.0	440	1.0603	0.625
No log	23.0	460	1.0404	0.6312
No log	24.0	480	0.8838	0.6937
0.4269	25.0	500	0.9280	0.6937
0.4269	26.0	520	0.9456	0.6937
0.4269	27.0	540	0.9640	0.6937
0.4269	28.0	560	0.9865	0.6937
0.4269	29.0	580	0.8900	0.7188
0.4269	30.0	600	0.9408	0.7063

Framework versions

• Transformers 4.33.2
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3