roberta_test_two_2

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>

roberta_test_two_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: 0.3803

accuracy

: 0.8535

f1

: 0.8478

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 | 0.4079 | 0.8430 | 0.8379 | | 0.5126 | 2.0 | 828 | 0.3970 | 0.8326 | 0.8342 | | 0.4152 | 3.0 | 1242 | 0.3803 | 0.8535 | 0.8478 | | 0.3846 | 4.0 | 1656 | 0.3840 | 0.8419 | 0.8406 | | 0.3562 | 5.0 | 2070 | 0.3963 | 0.8419 | 0.8415 |

Framework versions

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