metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-financial-time-period
results: []
distilbert-financial-time-period
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1907
- Accuracy: 0.9524
- F1: 0.9514
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 159 | 0.9372 | 0.7302 | 0.6664 |
| No log | 2.0 | 318 | 0.3961 | 0.9048 | 0.9011 |
| No log | 3.0 | 477 | 0.1855 | 0.9365 | 0.9354 |
| 0.7784 | 4.0 | 636 | 0.1987 | 0.9365 | 0.9354 |
| 0.7784 | 5.0 | 795 | 0.1881 | 0.9524 | 0.9514 |
| 0.7784 | 6.0 | 954 | 0.1907 | 0.9524 | 0.9514 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1