---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: unga-climate-classifier
  results: []
---

# ECCA climate classifier

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0936
- Accuracy: 0.9798
- F1 Macro: 0.9765
- Accuracy Balanced: 0.9751
- F1 Micro: 0.9798
- Precision Macro: 0.9780
- Recall Macro: 0.9751
- Precision Micro: 0.9798
- Recall Micro: 0.9798

## 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: 16
- eval_batch_size: 80
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Accuracy Balanced | F1 Micro | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
| No log        | 1.0   | 123  | 0.1778          | 0.9609   | 0.9543   | 0.9510            | 0.9609   | 0.9577          | 0.9510       | 0.9609          | 0.9609       |
| No log        | 2.0   | 246  | 0.1614          | 0.9680   | 0.9626   | 0.9593            | 0.9680   | 0.9661          | 0.9593       | 0.9680          | 0.9680       |
| No log        | 3.0   | 369  | 0.1598          | 0.9680   | 0.9626   | 0.9593            | 0.9680   | 0.9661          | 0.9593       | 0.9680          | 0.9680       |
| No log        | 4.0   | 492  | 0.1191          | 0.9703   | 0.9653   | 0.9610            | 0.9703   | 0.9699          | 0.9610       | 0.9703          | 0.9703       |
| 0.1357        | 5.0   | 615  | 0.1400          | 0.9727   | 0.9681   | 0.9638            | 0.9727   | 0.9727          | 0.9638       | 0.9727          | 0.9727       |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.6.0
- Tokenizers 0.15.1