finetuned_bert-base-on-IEMOCAP_3 – AI Model by minoosh | AlphaNeural AI

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minoosh/
finetuned_bert-base-on-IEMOCAP_3

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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finetuned_bert-base-on-IEMOCAP_3

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: 1.0342
Accuracy: 0.6490

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
1.2553	1.0	110	1.2256	0.4636
0.8935	2.0	220	0.9211	0.6355
0.7189	3.0	330	0.7761	0.7107
0.5676	4.0	440	0.8031	0.7210
0.3598	5.0	550	0.8454	0.7301
0.2774	6.0	660	0.8871	0.7153
0.2699	7.0	770	0.9372	0.7175
0.1963	8.0	880	0.9686	0.7244
0.2565	9.0	990	1.0099	0.7016
0.1849	10.0	1100	1.0425	0.7175
0.1769	11.0	1210	1.1145	0.7118
0.1727	12.0	1320	1.1316	0.7187
0.1132	13.0	1430	1.0963	0.7244
0.1314	14.0	1540	1.1908	0.7118
0.0833	15.0	1650	1.2133	0.7164
0.1378	16.0	1760	1.1971	0.7210
0.1067	17.0	1870	1.2330	0.7118
0.0539	18.0	1980	1.2246	0.7198
0.0718	19.0	2090	1.2364	0.7164
0.1036	20.0	2200	1.2446	0.7164

Framework versions

Transformers 4.30.1
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3