distilbert-base-uncased_3epoch6 – AI Model by dianamihalache27 | AlphaNeural AI

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dianamihalache27/
distilbert-base-uncased_3epoch6

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text-classification

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distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert-base-uncased_3epoch6

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

Loss: 2.5778
Accuracy: 0.7003
F1: 0.2925
Precision: 0.4526
Recall: 0.2161
Precision Sarcastic: 0.4526
Recall Sarcastic: 0.2161
F1 Sarcastic: 0.2925

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Precision Sarcastic	Recall Sarcastic	F1 Sarcastic
No log	1.0	174	2.6246	0.6974	0.3137	0.4486	0.2412	0.4486	0.2412	0.3137
No log	2.0	348	2.8307	0.7089	0.1789	0.4681	0.1106	0.4681	0.1106	0.1789
0.0054	3.0	522	2.6512	0.6787	0.4678	0.4455	0.4925	0.4455	0.4925	0.4678
0.0054	4.0	696	2.3964	0.7003	0.3247	0.4587	0.2513	0.4587	0.2513	0.3247
0.0054	5.0	870	2.5224	0.7003	0.3203	0.4579	0.2462	0.4579	0.2462	0.3203
0.0114	6.0	1044	2.5778	0.7003	0.2925	0.4526	0.2161	0.4526	0.2161	0.2925

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1