MTL-roberta-base – AI Model by jgammack | AlphaNeural AI

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MTL-roberta-base

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MTL-roberta-base

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

Loss: 1.4859

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: 2e-05
train_batch_size: 7
eval_batch_size: 7
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.8338	1.0	98	1.6750
1.7732	2.0	196	1.6229
1.7208	3.0	294	1.6131
1.6917	4.0	392	1.5936
1.6579	5.0	490	1.6183
1.6246	6.0	588	1.6015
1.6215	7.0	686	1.5248
1.5743	8.0	784	1.5454
1.5621	9.0	882	1.5925
1.5652	10.0	980	1.5213
1.5615	11.0	1078	1.4845
1.5349	12.0	1176	1.5443
1.5165	13.0	1274	1.5304
1.5164	14.0	1372	1.4773
1.5293	15.0	1470	1.5537

Framework versions

Transformers 4.16.2
Pytorch 1.10.0+cu111
Datasets 1.18.3
Tokenizers 0.11.0