| | --- |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: roberta-large-first |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # roberta-large-first |
| |
|
| | This model is a fine-tuned version of [rafalposwiata/deproberta-large-depression](https://huggingface.co/rafalposwiata/deproberta-large-depression) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.2025 |
| | - Accuracy: 0.8483 |
| | - F1: 0.9100 |
| |
|
| | ## 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: 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_steps: 500 |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | | No log | 1.0 | 469 | 0.3694 | 0.8783 | 0.9312 | |
| | | 0.3984 | 2.0 | 938 | 0.4488 | 0.87 | 0.9257 | |
| | | 0.3366 | 3.0 | 1407 | 0.5764 | 0.855 | 0.9141 | |
| | | 0.295 | 4.0 | 1876 | 0.7716 | 0.8533 | 0.9132 | |
| | | 0.1876 | 5.0 | 2345 | 0.8724 | 0.855 | 0.9148 | |
| | | 0.1378 | 6.0 | 2814 | 1.1717 | 0.825 | 0.8921 | |
| | | 0.0836 | 7.0 | 3283 | 1.0711 | 0.8367 | 0.9028 | |
| | | 0.043 | 8.0 | 3752 | 1.0807 | 0.8633 | 0.9202 | |
| | | 0.0402 | 9.0 | 4221 | 1.2285 | 0.8367 | 0.9024 | |
| | | 0.035 | 10.0 | 4690 | 1.2025 | 0.8483 | 0.9100 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.30.2 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.13.1 |
| | - Tokenizers 0.13.3 |
| | |
