distilbert-base-uncased-finetuned-emotion – AI Model by yspkm | AlphaNeural AI

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yspkm/
distilbert-base-uncased-finetuned-emotion

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert-base-uncased-finetuned-emotion

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

Loss: 0.1443
Accuracy: 0.9375
F1: 0.9378

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: 256
eval_batch_size: 256
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	63	0.8657	0.714	0.6520
No log	2.0	126	0.3186	0.9085	0.9076
No log	3.0	189	0.2032	0.928	0.9281
0.5856	4.0	252	0.1733	0.93	0.9301
0.5856	5.0	315	0.1578	0.937	0.9368
0.5856	6.0	378	0.1543	0.9335	0.9341
0.5856	7.0	441	0.1506	0.9345	0.9343
0.1139	8.0	504	0.1475	0.939	0.9396
0.1139	9.0	567	0.1444	0.9375	0.9374
0.1139	10.0	630	0.1443	0.9375	0.9378

Framework versions

Transformers 4.41.2
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1