roberta_suba_fixed_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: 0.3601

accuracy

: 0.8547

: 0.8489

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 | 414 | 0.3916 | 0.8384 | 0.8280 | | 0.5073 | 2.0 | 828 | 0.3771 | 0.8430 | 0.8427 | | 0.405 | 3.0 | 1242 | 0.3609 | 0.8628 | 0.8582 | | 0.3764 | 4.0 | 1656 | 0.3601 | 0.8547 | 0.8489 | | 0.3444 | 5.0 | 2070 | 0.3787 | 0.8488 | 0.8470 | | 0.3444 | 6.0 | 2484 | 0.3927 | 0.8442 | 0.8340 |

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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