levelc_no_2

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: 0.7667

accuracy

: 0.6714

: 0.6078

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 | 122 | 0.8572 | 0.6385 | 0.5792 | | No log | 2.0 | 244 | 0.7976 | 0.6620 | 0.5997 | | No log | 3.0 | 366 | 0.7667 | 0.6714 | 0.6078 | | No log | 4.0 | 488 | 0.7802 | 0.6714 | 0.6062 | | 0.6848 | 5.0 | 610 | 0.7765 | 0.6854 | 0.6272 |

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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distilbert/distilbert-base-uncased

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