---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: check-in-quality-classifier
  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. -->

# check-in-quality-classifier

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: 0.8464
- Accuracy: 0.7143
- F1: 0.6857
- Precision: 0.6746
- Recall: 0.7143

## 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: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 21   | 0.9602          | 0.2857   | 0.1270 | 0.0816    | 0.2857 |
| No log        | 2.0   | 42   | 0.8913          | 0.5238   | 0.4891 | 0.6302    | 0.5238 |
| No log        | 3.0   | 63   | 0.8464          | 0.7143   | 0.6857 | 0.6746    | 0.7143 |


### Framework versions

- Transformers 4.56.2
- Pytorch 2.8.0
- Datasets 4.0.0
- Tokenizers 0.22.1