| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: climatebert/distilroberta-base-climate-f |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: climatebert-bin |
| 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. --> |
|
|
| # climatebert-bin |
|
|
| This model is a fine-tuned version of [climatebert/distilroberta-base-climate-f](https://huggingface.co/climatebert/distilroberta-base-climate-f) on an unknown dataset. |
| It achieves the following results on the final test set: |
| - Loss: 0.548 |
| - F1 Macro: 0.9156 |
| - Accuracy: 0.9224 |
|
|
| ## 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: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 20 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | F1 Macro | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
| | 1.3366 | 1.0 | 17 | 1.2471 | 0.3958 | 0.6552 | |
| | 1.1692 | 2.0 | 34 | 1.0087 | 0.5175 | 0.6983 | |
| | 0.7289 | 3.0 | 51 | 0.4934 | 0.8916 | 0.9052 | |
| | 0.5135 | 4.0 | 68 | 0.4027 | 0.9343 | 0.9397 | |
| | 0.2444 | 5.0 | 85 | 0.3297 | 0.9237 | 0.9310 | |
| | 0.1078 | **6.0** | 102 | 0.3546 | **0.9428** | 0.9483 | |
| | 0.0307 | 7.0 | 119 | 0.5146 | 0.9254 | 0.9310 | |
| | 0.0193 | 8.0 | 136 | 0.5244 | 0.9336 | 0.9397 | |
| | 0.0277 | 9.0 | 153 | 0.8077 | 0.9076 | 0.9138 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.8.5 |
| - Tokenizers 0.22.2 |
| |
