levela_huge_no_3

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: 0.7264

accuracy

: 0.7183

: 0.6879

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 | 0.8245 | 0.6573 | 0.5970 | | No log | 2.0 | 244 | 0.7692 | 0.6667 | 0.6038 | | No log | 3.0 | 366 | 0.7409 | 0.6808 | 0.6237 | | No log | 4.0 | 488 | 0.7526 | 0.6948 | 0.6353 | | 0.684 | 5.0 | 610 | 0.7363 | 0.7042 | 0.6525 | | 0.684 | 6.0 | 732 | 0.7284 | 0.6854 | 0.6242 | | 0.684 | 7.0 | 854 | 0.7264 | 0.7183 | 0.6879 | | 0.684 | 8.0 | 976 | 0.7313 | 0.7324 | 0.7083 | | 0.513 | 9.0 | 1098 | 0.7510 | 0.7230 | 0.7054 |

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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