| --- |
| license: apache-2.0 |
| base_model: bert-base-uncased |
| tags: |
| - generated_from_trainer |
| datasets: |
| - arxiv_dataset |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: test_implementation |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: arxiv_dataset |
| type: arxiv_dataset |
| config: default |
| split: train |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.5925759148656968 |
| - name: Precision |
| type: precision |
| value: 0.00904383876000648 |
| - name: Recall |
| type: recall |
| value: 0.37505752416014726 |
| - name: F1 |
| type: f1 |
| value: 0.017661795045162184 |
| --- |
| |
| <!-- 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. --> |
|
|
| # test_implementation |
| |
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the arxiv_dataset dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6736 |
| - Accuracy: 0.5926 |
| - Precision: 0.0090 |
| - Recall: 0.3751 |
| - F1: 0.0177 |
| - Hamming: 0.4074 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - training_steps: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Hamming | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:| |
| | 0.7077 | 0.0 | 5 | 0.6857 | 0.5529 | 0.0089 | 0.4040 | 0.0173 | 0.4471 | |
| | 0.6801 | 0.0 | 10 | 0.6736 | 0.5926 | 0.0090 | 0.3751 | 0.0177 | 0.4074 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.37.2 |
| - Pytorch 1.12.1+cu113 |
| - Datasets 2.16.1 |
| - Tokenizers 0.15.1 |
| |
