---
license: apache-2.0
tags:
- generated_from_keras_callback
base_model: bert-base-uncased
model-index:
- name: nlp-esg-scoring/bert-base-finetuned-esg-gri-clean
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# nlp-esg-scoring/bert-base-finetuned-esg-gri-clean

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.9511
- Validation Loss: 1.5293
- Epoch: 9

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -797, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 1.9468     | 1.5190          | 0     |
| 1.9433     | 1.5186          | 1     |
| 1.9569     | 1.4843          | 2     |
| 1.9510     | 1.5563          | 3     |
| 1.9451     | 1.5308          | 4     |
| 1.9576     | 1.5209          | 5     |
| 1.9464     | 1.5324          | 6     |
| 1.9525     | 1.5168          | 7     |
| 1.9488     | 1.5340          | 8     |
| 1.9511     | 1.5293          | 9     |


### Framework versions

- Transformers 4.20.1
- TensorFlow 2.8.2
- Datasets 2.3.2
- Tokenizers 0.12.1