distilbert-perigon-200k – AI Model by judy93536 | AlphaNeural AI

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judy93536/
distilbert-perigon-200k

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distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert-base-uncased-finetuned-news-lr5

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: 1.1744

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: 7.5e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.17
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss
2.568	1.0	5323	1.9294
1.8742	2.0	10646	1.6656
1.6837	3.0	15969	1.5462
1.5855	4.0	21292	1.4742
1.5058	5.0	26615	1.4183
1.4472	6.0	31938	1.3763
1.4049	7.0	37261	1.3439
1.3697	8.0	42584	1.3225
1.339	9.0	47907	1.3010
1.3119	10.0	53230	1.2795
1.2886	11.0	58553	1.2613
1.2676	12.0	63876	1.2451
1.2489	13.0	69199	1.2309
1.2337	14.0	74522	1.2207
1.2171	15.0	79845	1.2094
1.2009	16.0	85168	1.1997
1.1889	17.0	90491	1.1912
1.177	18.0	95814	1.1826
1.1679	19.0	101137	1.1780
1.162	20.0	106460	1.1714

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3