metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: distilBERT_finetuned_esg
results: []
distilBERT_finetuned_esg
This model is a fine-tuned version of 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