|
--- |
|
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 |
|
|
