metadata

license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: distilbert-base-uncased-finetuned-ft1500_norm500_aug4
    results: []

distilbert-base-uncased-finetuned-ft1500_norm500_aug4

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: 1.5706
Mse: 3.1412
Mae: 1.0811
R2: 0.3860
Accuracy: 0.4382

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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Mse	Mae	R2	Accuracy
1.1391	1.0	3952	1.5706	3.1412	1.0811	0.3860	0.4382

Framework versions

Transformers 4.21.1
Pytorch 1.12.0+cu113
Datasets 2.4.0
Tokenizers 0.12.1