BERiT_2000_ls_.2 – AI Model by gngpostalsrvc | AlphaNeural AI

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BERiT_2000_ls_.2

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BERiT_2000_ls

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

Loss: 6.9311

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
label_smoothing_factor: 0.2

Training results

Training Loss	Epoch	Step	Validation Loss
7.0431	0.19	500	6.9715
6.9481	0.39	1000	6.9600
6.9487	0.58	1500	6.9444
6.9495	0.77	2000	6.9505
6.9373	0.97	2500	6.9556
6.9332	1.16	3000	6.9371
6.9295	1.36	3500	6.9256
6.9367	1.55	4000	6.9137
6.9387	1.74	4500	6.9337
6.9237	1.94	5000	6.9251
6.9363	2.13	5500	6.9490
6.9591	2.32	6000	6.9261
6.9066	2.52	6500	6.9322
6.9385	2.71	7000	6.9222
6.9293	2.9	7500	6.9311

Framework versions

Transformers 4.24.0
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.2