---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: nosql-identifier-distilbert
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# nosql-identifier-distilbert

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1660
- Accuracy: 0.95

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 40   | 0.4882          | 0.875    |
| No log        | 2.0   | 80   | 0.2036          | 0.975    |
| No log        | 3.0   | 120  | 0.1521          | 0.975    |
| No log        | 4.0   | 160  | 0.2719          | 0.875    |
| No log        | 5.0   | 200  | 0.0980          | 0.975    |
| No log        | 6.0   | 240  | 0.1752          | 0.95     |
| No log        | 7.0   | 280  | 0.3715          | 0.9      |
| No log        | 8.0   | 320  | 0.1640          | 0.95     |
| No log        | 9.0   | 360  | 0.1756          | 0.95     |
| No log        | 10.0  | 400  | 0.1386          | 0.975    |
| No log        | 11.0  | 440  | 0.2747          | 0.95     |
| No log        | 12.0  | 480  | 0.2302          | 0.95     |
| 0.2758        | 13.0  | 520  | 0.2518          | 0.95     |
| 0.2758        | 14.0  | 560  | 0.1722          | 0.95     |
| 0.2758        | 15.0  | 600  | 0.1660          | 0.95     |


### Framework versions

- Transformers 4.31.0
- Pytorch 1.12.1+cu113
- Datasets 2.13.1
- Tokenizers 0.11.0