metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-custom
results: []
widget:
- text: 2020/01/27 New water filter $210.00
example_title: Item line 1
- text: 2024/04/04 supply and fit new timer knob and thermostat $03.35
example_title: Item line 2
- text: 2024/04/01 callout 110.00
example_title: Item line 3
distilbert-base-uncased-custom
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0006
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 50 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 2.0 | 100 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 3.0 | 150 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.14.1
- Tokenizers 0.19.1