---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: distilBERT_finetuned_esg
  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. -->

# distilBERT_finetuned_esg

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co./distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2591
- F1: 0.6296
- Roc Auc: 0.7569
- Accuracy: 0.3824

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 77   | 0.3731          | 0.4    | 0.6322  | 0.2647   |
| No log        | 2.0   | 154  | 0.3158          | 0.2342 | 0.5651  | 0.1324   |
| No log        | 3.0   | 231  | 0.2773          | 0.5    | 0.6791  | 0.3382   |
| No log        | 4.0   | 308  | 0.2636          | 0.6049 | 0.7442  | 0.3382   |
| No log        | 5.0   | 385  | 0.2591          | 0.6296 | 0.7569  | 0.3824   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0