test_reform

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test_reform

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: 0.3630

accuracy

: 0.8488

f1

: 0.8453

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

| Training Loss | Epoch | Step | Validation Loss |

accuracy

|

f1

| |:-------------:|:-----:|:----:|:---------------:|:------------:|:------:| | No log | 1.0 | 414 | 0.3853 | 0.8477 | 0.8392 | | 0.4858 | 2.0 | 828 | 0.3742 | 0.8407 | 0.8402 | | 0.3966 | 3.0 | 1242 | 0.3653 | 0.8535 | 0.8475 | | 0.366 | 4.0 | 1656 | 0.3630 | 0.8488 | 0.8453 | | 0.331 | 5.0 | 2070 | 0.3892 | 0.8372 | 0.8376 | | 0.331 | 6.0 | 2484 | 0.4021 | 0.8488 | 0.8415 |

Framework versions

• Transformers 4.45.2
• Pytorch 2.5.0+cu124
• Datasets 3.0.1
• Tokenizers 0.20.1