finetuned_bert-base-on-IEMOCAP_2 – AI Model by minoosh | AlphaNeural AI

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minoosh/
finetuned_bert-base-on-IEMOCAP_2

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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finetuned_bert-base-on-IEMOCAP_2

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

Loss: 1.3186
Accuracy: 0.7410

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.3127	1.0	113	1.2620	0.4192
0.957	2.0	226	0.9294	0.6095
0.6409	3.0	339	0.8338	0.6969
0.5966	4.0	452	0.8386	0.6958
0.3725	5.0	565	0.8635	0.7035
0.3556	6.0	678	0.9218	0.7069
0.2466	7.0	791	0.9679	0.6914
0.1737	8.0	904	1.1180	0.6869
0.1694	9.0	1017	1.1068	0.6947
0.1843	10.0	1130	1.1409	0.6903
0.1747	11.0	1243	1.1143	0.7080
0.1387	12.0	1356	1.2127	0.6991
0.1524	13.0	1469	1.2309	0.7069
0.1113	14.0	1582	1.2382	0.7113
0.1278	15.0	1695	1.3048	0.7124
0.1214	16.0	1808	1.3267	0.7146
0.1965	17.0	1921	1.3726	0.7013
0.1227	18.0	2034	1.3371	0.7168
0.1014	19.0	2147	1.3508	0.7124
0.1028	20.0	2260	1.3585	0.7080

Framework versions

Transformers 4.30.1
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3