---
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: 2.2623
- Accuracy Thresh: 0.9380

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|
| 1.6787        | 1.0   | 845  | 0.8456          | 0.8252          |
| 0.749         | 2.0   | 1690 | 0.8447          | 0.8887          |
| 0.5849        | 3.0   | 2535 | 0.9489          | 0.8968          |
| 0.4312        | 4.0   | 3380 | 1.1496          | 0.9084          |
| 0.3469        | 5.0   | 4225 | 1.4157          | 0.9260          |
| 0.2633        | 6.0   | 5070 | 1.8314          | 0.9277          |
| 0.2498        | 7.0   | 5915 | 1.9466          | 0.9355          |
| 0.1782        | 8.0   | 6760 | 1.9609          | 0.9336          |
| 0.1763        | 9.0   | 7605 | 2.2429          | 0.9350          |
| 0.1489        | 10.0  | 8450 | 2.2623          | 0.9380          |


### Framework versions

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