---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-q-classifier-2
  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. -->

# distilbert-q-classifier-2

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2779
- Accuracy: 0.9421
- Precision Weighted: 0.9429
- Recall Weighted: 0.9421
- F1 Weighted: 0.9421
- Precision Macro: 0.9429
- Recall Macro: 0.9421
- F1 Macro: 0.9421

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Weighted | Recall Weighted | F1 Weighted | Precision Macro | Recall Macro | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------------------:|:---------------:|:-----------:|:---------------:|:------------:|:--------:|
| No log        | 1.0   | 48   | 0.2252          | 0.9144   | 0.9144             | 0.9144          | 0.9144      | 0.9144          | 0.9144       | 0.9144   |
| No log        | 2.0   | 96   | 0.1682          | 0.9329   | 0.9333             | 0.9329          | 0.9329      | 0.9333          | 0.9329       | 0.9329   |
| No log        | 3.0   | 144  | 0.2251          | 0.9236   | 0.9269             | 0.9236          | 0.9235      | 0.9269          | 0.9236       | 0.9235   |
| No log        | 4.0   | 192  | 0.2421          | 0.9352   | 0.9376             | 0.9352          | 0.9351      | 0.9376          | 0.9352       | 0.9351   |
| No log        | 5.0   | 240  | 0.2138          | 0.9375   | 0.9383             | 0.9375          | 0.9375      | 0.9383          | 0.9375       | 0.9375   |
| No log        | 6.0   | 288  | 0.2165          | 0.9398   | 0.9399             | 0.9398          | 0.9398      | 0.9399          | 0.9398       | 0.9398   |
| No log        | 7.0   | 336  | 0.2470          | 0.9398   | 0.9408             | 0.9398          | 0.9398      | 0.9408          | 0.9398       | 0.9398   |
| No log        | 8.0   | 384  | 0.2509          | 0.9352   | 0.9353             | 0.9352          | 0.9352      | 0.9353          | 0.9352       | 0.9352   |
| No log        | 9.0   | 432  | 0.2686          | 0.9352   | 0.9355             | 0.9352          | 0.9352      | 0.9355          | 0.9352       | 0.9352   |
| No log        | 10.0  | 480  | 0.2779          | 0.9421   | 0.9429             | 0.9421          | 0.9421      | 0.9429          | 0.9421       | 0.9421   |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.19.1