BERiT_7000 – AI Model by gngpostalsrvc | AlphaNeural AI

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BERiT_7000

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BERiT_7000

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

Loss: 7.5916

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
7.9484	0.19	500	7.8474
7.7968	0.39	1000	7.7020
7.6992	0.58	1500	7.6949
7.656	0.77	2000	7.6922
7.68	0.97	2500	7.6863
7.5952	1.16	3000	7.6523
7.6441	1.36	3500	7.6523
7.6178	1.55	4000	7.6128
7.5977	1.74	4500	7.6556
7.6087	1.94	5000	7.5990
7.5734	2.13	5500	7.5997
7.566	2.32	6000	7.5961
7.5715	2.52	6500	7.5505
7.5604	2.71	7000	7.5788
7.5749	2.9	7500	7.5916

Framework versions

Transformers 4.24.0
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.2