---
license: mit
tags:
- generated_from_trainer
base_model: xlm-roberta-base
model-index:
- name: job-listing-relevance-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-listing-relevance-model

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1649

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7435        | 0.43  | 50   | 0.6889          |
| 0.3222        | 0.87  | 100  | 0.2906          |
| 0.2573        | 1.3   | 150  | 0.1937          |
| 0.1205        | 1.74  | 200  | 0.1411          |
| 0.1586        | 2.17  | 250  | 0.2008          |
| 0.0755        | 2.61  | 300  | 0.1926          |
| 0.062         | 3.04  | 350  | 0.2257          |
| 0.0644        | 3.48  | 400  | 0.1497          |
| 0.1034        | 3.91  | 450  | 0.1561          |
| 0.008         | 4.35  | 500  | 0.2067          |
| 0.0616        | 4.78  | 550  | 0.2067          |
| 0.0766        | 5.22  | 600  | 0.1494          |
| 0.0029        | 5.65  | 650  | 0.2078          |
| 0.1076        | 6.09  | 700  | 0.1669          |
| 0.0025        | 6.52  | 750  | 0.1564          |
| 0.0498        | 6.95  | 800  | 0.2355          |
| 0.0011        | 7.39  | 850  | 0.1652          |
| 0.0271        | 7.82  | 900  | 0.1731          |
| 0.012         | 8.26  | 950  | 0.1590          |
| 0.0257        | 8.69  | 1000 | 0.1638          |
| 0.0009        | 9.13  | 1050 | 0.1851          |
| 0.0013        | 9.56  | 1100 | 0.1613          |
| 0.0015        | 10.0  | 1150 | 0.1649          |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 2.0.0
- Tokenizers 0.11.6