---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Job_compatibility_model
  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. -->

# Job_compatibility_model

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6238
- Accuracy: 0.8598

## 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: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 32   | 0.6922          | 0.5      |
| No log        | 2.0   | 64   | 0.6509          | 0.6238   |
| No log        | 3.0   | 96   | 0.4218          | 0.8411   |
| No log        | 4.0   | 128  | 0.3622          | 0.8481   |
| No log        | 5.0   | 160  | 0.3383          | 0.8645   |
| No log        | 6.0   | 192  | 0.3626          | 0.8528   |
| No log        | 7.0   | 224  | 0.3939          | 0.8621   |
| No log        | 8.0   | 256  | 0.4223          | 0.8715   |
| No log        | 9.0   | 288  | 0.4271          | 0.8692   |
| No log        | 10.0  | 320  | 0.4869          | 0.8621   |
| No log        | 11.0  | 352  | 0.5057          | 0.8645   |
| No log        | 12.0  | 384  | 0.5702          | 0.8528   |
| No log        | 13.0  | 416  | 0.5277          | 0.8692   |
| No log        | 14.0  | 448  | 0.5228          | 0.8785   |
| No log        | 15.0  | 480  | 0.5332          | 0.8762   |
| 0.2235        | 16.0  | 512  | 0.5859          | 0.8715   |
| 0.2235        | 17.0  | 544  | 0.5938          | 0.8762   |
| 0.2235        | 18.0  | 576  | 0.6005          | 0.8715   |
| 0.2235        | 19.0  | 608  | 0.5941          | 0.8715   |
| 0.2235        | 20.0  | 640  | 0.6115          | 0.8762   |
| 0.2235        | 21.0  | 672  | 0.6098          | 0.8715   |
| 0.2235        | 22.0  | 704  | 0.6091          | 0.8715   |
| 0.2235        | 23.0  | 736  | 0.6223          | 0.8621   |
| 0.2235        | 24.0  | 768  | 0.6309          | 0.8598   |
| 0.2235        | 25.0  | 800  | 0.6238          | 0.8598   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2