---
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: 2.4463
- Accuracy Thresh: 0.9341

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|
| 1.9127        | 1.0   | 851  | 0.9906          | 0.8086          |
| 0.8577        | 2.0   | 1702 | 1.0184          | 0.8701          |
| 0.6468        | 3.0   | 2553 | 1.0851          | 0.8901          |
| 0.494         | 4.0   | 3404 | 1.2894          | 0.9122          |
| 0.3875        | 5.0   | 4255 | 1.6629          | 0.9232          |
| 0.3422        | 6.0   | 5106 | 1.7630          | 0.9212          |
| 0.3121        | 7.0   | 5957 | 1.9873          | 0.9274          |
| 0.283         | 8.0   | 6808 | 2.3035          | 0.9328          |
| 0.2385        | 9.0   | 7659 | 2.4651          | 0.9338          |
| 0.1973        | 10.0  | 8510 | 2.4463          | 0.9341          |


### Framework versions

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