roberta_test_higher_sentiment_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: 0.7152

accuracy

: 0.8035

: 0.8055

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 | 2.1700 | 0.7140 | 0.6107 | | 3.0791 | 2.0 | 828 | 1.8606 | 0.6674 | 0.5934 | | 2.2628 | 3.0 | 1242 | 1.6506 | 0.6244 | 0.5875 | | 1.9009 | 4.0 | 1656 | 1.5491 | 0.5907 | 0.5741 | | 1.7106 | 5.0 | 2070 | 1.3944 | 0.6616 | 0.6175 | | 1.7106 | 6.0 | 2484 | 1.2659 | 0.7093 | 0.6405 | | 1.4298 | 7.0 | 2898 | 1.0533 | 0.7128 | 0.6614 | | 1.088 | 8.0 | 3312 | 0.8825 | 0.7128 | 0.6797 | | 0.8339 | 9.0 | 3726 | 0.7896 | 0.7267 | 0.7034 | | 0.6551 | 10.0 | 4140 | 0.7736 | 0.7360 | 0.7306 | | 0.5637 | 11.0 | 4554 | 0.7400 | 0.8070 | 0.8025 | | 0.5637 | 12.0 | 4968 | 0.7152 | 0.8035 | 0.8055 | | 0.4821 | 13.0 | 5382 | 0.7421 | 0.8070 | 0.8072 | | 0.4184 | 14.0 | 5796 | 0.7307 | 0.8023 | 0.8038 |

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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