---
license: apache-2.0
base_model: climatebert/distilroberta-base-climate-f
tags:
- generated_from_trainer
model-index:
- name: SECTOR-multilabel-climatebert
  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. -->

# SECTOR-multilabel-climatebert

This model is a fine-tuned version of [climatebert/distilroberta-base-climate-f](https://huggingface.co/climatebert/distilroberta-base-climate-f) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6028
- Precision-micro: 0.6395
- Precision-samples: 0.7543
- Precision-weighted: 0.6475
- Recall-micro: 0.7762
- Recall-samples: 0.8583
- Recall-weighted: 0.7762
- F1-micro: 0.7012
- F1-samples: 0.7655
- F1-weighted: 0.7041

## 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: 9.07e-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: 7

### 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:-----------------:|:------------------:|:------------:|:--------------:|:---------------:|:--------:|:----------:|:-----------:|
| 0.6978        | 1.0   | 633  | 0.5968          | 0.3948          | 0.5274            | 0.4982             | 0.7873       | 0.8675         | 0.7873          | 0.5259   | 0.5996     | 0.5793      |
| 0.485         | 2.0   | 1266 | 0.5255          | 0.5089          | 0.6365            | 0.5469             | 0.7984       | 0.8749         | 0.7984          | 0.6216   | 0.6907     | 0.6384      |
| 0.3657        | 3.0   | 1899 | 0.5248          | 0.4984          | 0.6617            | 0.5397             | 0.8141       | 0.8769         | 0.8141          | 0.6183   | 0.7066     | 0.6393      |
| 0.2585        | 4.0   | 2532 | 0.5457          | 0.5807          | 0.7148            | 0.5992             | 0.8007       | 0.8752         | 0.8007          | 0.6732   | 0.7449     | 0.6813      |
| 0.1841        | 5.0   | 3165 | 0.5551          | 0.6016          | 0.7426            | 0.6192             | 0.7937       | 0.8677         | 0.7937          | 0.6844   | 0.7590     | 0.6917      |
| 0.1359        | 6.0   | 3798 | 0.5913          | 0.6349          | 0.7506            | 0.6449             | 0.7844       | 0.8676         | 0.7844          | 0.7018   | 0.7667     | 0.7057      |
| 0.1133        | 7.0   | 4431 | 0.6028          | 0.6395          | 0.7543            | 0.6475             | 0.7762       | 0.8583         | 0.7762          | 0.7012   | 0.7655     | 0.7041      |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2