levelb_no_1

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2617

accuracy

: 0.8917

: 0.8744

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-06
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: 50

Training results

accuracy

| |:-------------:|:-----:|:----:|:---------------:|:------------:|:------:| | No log | 1.0 | 138 | 0.2981 | 0.8875 | 0.8346 | | No log | 2.0 | 276 | 0.2752 | 0.8875 | 0.8346 | | No log | 3.0 | 414 | 0.2642 | 0.8875 | 0.8421 | | 0.3304 | 4.0 | 552 | 0.2627 | 0.8875 | 0.8678 | | 0.3304 | 5.0 | 690 | 0.2617 | 0.8917 | 0.8744 | | 0.3304 | 6.0 | 828 | 0.2722 | 0.8917 | 0.8832 | | 0.3304 | 7.0 | 966 | 0.2825 | 0.8833 | 0.8714 |

Framework versions

Transformers 4.45.2
Pytorch 2.5.0+cu124
Datasets 3.0.1
Tokenizers 0.20.1

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Model size

66.4M params

Tensor type

F32

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