distil-i – AI Model by paola-md | AlphaNeural AI

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distil-i

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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distil-i

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

Loss: 0.6252
Rmse: 0.7907
Mse: 0.6252
Mae: 0.6061

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: 32
eval_batch_size: 32
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	Rmse	Mse	Mae
0.7417	1.0	492	0.7164	0.8464	0.7164	0.5983
0.5948	2.0	984	0.6469	0.8043	0.6469	0.5840
0.5849	3.0	1476	0.6068	0.7790	0.6068	0.6027
0.5839	4.0	1968	0.6220	0.7887	0.6220	0.5847
0.5786	5.0	2460	0.6252	0.7907	0.6252	0.6061

Framework versions

Transformers 4.19.0.dev0
Pytorch 1.9.0+cu111
Datasets 2.4.0
Tokenizers 0.12.1