distilbert-base-uncased-finetuned-resume – AI Model by vasu11 | AlphaNeural AI

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vasu11/
distilbert-base-uncased-finetuned-resume

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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-resume

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7572
Accuracy: 0.6121
Precision: 0.5993
Recall: 0.5837
F1: 0.5817

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: 3e-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
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.961	1.0	583	0.7683	0.6508	0.6194	0.5758	0.5509
0.7218	2.0	1166	0.7392	0.6424	0.6484	0.5936	0.5577
0.6682	3.0	1749	0.7518	0.6358	0.5780	0.6620	0.6089
0.6262	4.0	2332	0.7457	0.6199	0.5959	0.6417	0.5964
0.59	5.0	2915	0.7572	0.6121	0.5993	0.5837	0.5817

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.1