---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: aift-model-review-multiple-label-classification
  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. -->

# aift-model-review-multiple-label-classification

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: 3.6138
- Accuracy Thresh: 0.9404

## 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
- distributed_type: tpu
- 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 Thresh |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|
| 0.2497        | 1.0   | 845  | 2.3781          | 0.9358          |
| 0.253         | 2.0   | 1690 | 2.4414          | 0.9311          |
| 0.2419        | 3.0   | 2535 | 3.1739          | 0.9374          |
| 0.1993        | 4.0   | 3380 | 2.9218          | 0.9409          |
| 0.158         | 5.0   | 4225 | 3.5374          | 0.9395          |
| 0.142         | 6.0   | 5070 | 3.8794          | 0.9398          |
| 0.1521        | 7.0   | 5915 | 3.7040          | 0.9399          |
| 0.1409        | 8.0   | 6760 | 3.5779          | 0.9401          |
| 0.1336        | 9.0   | 7605 | 3.7745          | 0.9413          |
| 0.1144        | 10.0  | 8450 | 3.6138          | 0.9404          |


### Framework versions

- Transformers 4.37.1
- Pytorch 2.0.0+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0