nlp_bert_emo_classifier – AI Model by Jateendra | AlphaNeural AI

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Jateendra/
nlp_bert_emo_classifier

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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nlp_bert_emo_classifier

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

Loss: 0.2791

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss
0.8887	0.25	500	0.4212
0.3216	0.5	1000	0.3192
0.2649	0.75	1500	0.2746
0.2535	1.0	2000	0.2573
0.163	1.25	2500	0.2157
0.1868	1.5	3000	0.2118
0.1258	1.75	3500	0.2319
0.1726	2.0	4000	0.1853
0.1035	2.25	4500	0.2146
0.1135	2.5	5000	0.2207
0.1117	2.75	5500	0.2496
0.1145	3.0	6000	0.2482
0.0726	3.25	6500	0.2654
0.0828	3.5	7000	0.2622
0.0817	3.75	7500	0.2775
0.0689	4.0	8000	0.2791

Framework versions

Transformers 4.15.0
Pytorch 1.12.0+cu113
Datasets 2.4.0
Tokenizers 0.10.3