distilbert-base-uncased-finetuned-recruitment-exp – AI Model by reyhanemyr | AlphaNeural AI

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reyhanemyr/
distilbert-base-uncased-finetuned-recruitment-exp

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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distilbert-base-uncased-finetuned-recruitment-exp

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: 0.1742
Precision: 0.6204
Recall: 0.6855
F1: 0.6513
Accuracy: 0.9561

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: 5e-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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	17	0.5203	0.0	0.0	0.0	0.8991
No log	2.0	34	0.3797	0.2979	0.0277	0.0507	0.9030
No log	3.0	51	0.2983	0.3171	0.4194	0.3612	0.9222
No log	4.0	68	0.2321	0.4219	0.4916	0.4541	0.9375
No log	5.0	85	0.2100	0.5076	0.5262	0.5168	0.9453
No log	6.0	102	0.1899	0.5174	0.5885	0.5507	0.9506
No log	7.0	119	0.1775	0.5395	0.6350	0.5834	0.9509
No log	8.0	136	0.1817	0.6282	0.6617	0.6445	0.9550
No log	9.0	153	0.1775	0.6262	0.6726	0.6485	0.9558
No log	10.0	170	0.1742	0.6204	0.6855	0.6513	0.9561

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3