This model is a fine-tuned version of distilbert-base-uncased on the nlpaueb/finer-139 dataset. It achieves the following results on the evaluation set:

Loss: 0.0027
Accuracy: 0.9992
Precision: 0.9992
Recall: 0.9991
F1: 0.9991
Classification Report: precision recall f1-score support

DebtInstrumentBasisSpreadOnVariableRate1 0.63 0.92 0.75 3532 DebtInstrumentInterestRateStatedPercentage 1.00 1.00 1.00 5174933 LineOfCreditFacilityMaximumBorrowingCapacity 0.43 0.89 0.58 1346
```
                             micro avg       1.00      1.00      1.00   5179811
                             macro avg       0.69      0.94      0.78   5179811
                          weighted avg       1.00      1.00      1.00   5179811
```

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: 5e-05
train_batch_size: 192
eval_batch_size: 192
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Classification Report
0.0097	1.3514	500	0.0026	0.9991	0.9991	0.9990	0.9991	precision recall f1-score support

DebtInstrumentBasisSpreadOnVariableRate1 0.57 0.89 0.70 3532

DebtInstrumentInterestRateStatedPercentage 1.00 1.00 1.00 5174933 LineOfCreditFacilityMaximumBorrowingCapacity 0.45 0.79 0.57 1346

                               micro avg       1.00      1.00      1.00   5179811
                               macro avg       0.67      0.89      0.76   5179811
                            weighted avg       1.00      1.00      1.00   5179811

| | 0.0064 | 2.7027 | 1000 | 0.0026 | 0.9991 | 0.9991 | 0.9990 | 0.9990 | precision recall f1-score support

DebtInstrumentBasisSpreadOnVariableRate1 0.59 0.92 0.72 3532

DebtInstrumentInterestRateStatedPercentage 1.00 1.00 1.00 5174933 LineOfCreditFacilityMaximumBorrowingCapacity 0.42 0.85 0.57 1346

                               micro avg       1.00      1.00      1.00   5179811
                               macro avg       0.67      0.92      0.76   5179811
                            weighted avg       1.00      1.00      1.00   5179811

| | 0.0044 | 4.0541 | 1500 | 0.0027 | 0.9992 | 0.9992 | 0.9991 | 0.9991 | precision recall f1-score support

DebtInstrumentBasisSpreadOnVariableRate1 0.63 0.92 0.75 3532

DebtInstrumentInterestRateStatedPercentage 1.00 1.00 1.00 5174933 LineOfCreditFacilityMaximumBorrowingCapacity 0.43 0.89 0.58 1346

                               micro avg       1.00      1.00      1.00   5179811
                               macro avg       0.69      0.94      0.78   5179811
                            weighted avg       1.00      1.00      1.00   5179811

Framework versions

Transformers 4.46.3
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.20.3

martindevoto/finer_ner_finetuning

finer_ner_finetuning

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

martindevoto/
finer_ner_finetuning