metadata
license: apache-2.0
base_model: climatebert/distilroberta-base-climate-f
tags:
- generated_from_trainer
model-index:
- name: CONDITIONAL-multilabel-climatebert
results: []
CONDITIONAL-multilabel-climatebert
This model is a fine-tuned version of climatebert/distilroberta-base-climate-f on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5460
- Precision-micro: 0.5020
- Precision-samples: 0.1954
- Precision-weighted: 0.5047
- Recall-micro: 0.7530
- Recall-samples: 0.1937
- Recall-weighted: 0.7530
- F1-micro: 0.6024
- F1-samples: 0.1927
- F1-weighted: 0.6033
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: 6.03e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 300
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision-micro | Precision-samples | Precision-weighted | Recall-micro | Recall-samples | Recall-weighted | F1-micro | F1-samples | F1-weighted |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.5644 | 1.0 | 369 | 0.4161 | 0.3642 | 0.1391 | 0.4167 | 0.5640 | 0.1416 | 0.5640 | 0.4426 | 0.1389 | 0.4372 |
| 0.429 | 2.0 | 738 | 0.3616 | 0.4420 | 0.1803 | 0.4794 | 0.6860 | 0.1769 | 0.6860 | 0.5376 | 0.1768 | 0.5473 |
| 0.2657 | 3.0 | 1107 | 0.4233 | 0.4126 | 0.1950 | 0.4229 | 0.7774 | 0.1987 | 0.7774 | 0.5391 | 0.1944 | 0.5418 |
| 0.1482 | 4.0 | 1476 | 0.4301 | 0.4910 | 0.1891 | 0.4944 | 0.7470 | 0.1908 | 0.7470 | 0.5925 | 0.1882 | 0.5924 |
| 0.069 | 5.0 | 1845 | 0.5016 | 0.5126 | 0.1920 | 0.5193 | 0.7439 | 0.1912 | 0.7439 | 0.6070 | 0.1899 | 0.6090 |
| 0.0353 | 6.0 | 2214 | 0.5460 | 0.5020 | 0.1954 | 0.5047 | 0.7530 | 0.1937 | 0.7530 | 0.6024 | 0.1927 | 0.6033 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2