---
license: mit
tags:
- generated_from_trainer
model-index:
- name: relevant_profession
  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. -->

# relevant_profession

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: 0.8640
- Acc At K: 0.9666
- Acc: 0.7152

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Acc At K | Acc    |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|
| 3.6523        | 0.5   | 18304  | 2.1025          | 0.8154   | 0.5818 |
| 1.7365        | 1.0   | 36608  | 1.4014          | 0.9097   | 0.6590 |
| 1.2636        | 1.5   | 54912  | 1.1711          | 0.9350   | 0.6845 |
| 1.092         | 2.0   | 73216  | 1.0605          | 0.9473   | 0.6931 |
| 0.9662        | 2.5   | 91520  | 1.0046          | 0.9533   | 0.7012 |
| 0.9233        | 3.0   | 109824 | 0.9643          | 0.9573   | 0.7025 |
| 0.8521        | 3.5   | 128128 | 0.9436          | 0.9594   | 0.7060 |
| 0.8334        | 4.0   | 146432 | 0.9189          | 0.9616   | 0.7078 |
| 0.7845        | 4.5   | 164736 | 0.9082          | 0.9631   | 0.7091 |
| 0.7754        | 5.0   | 183040 | 0.8953          | 0.9639   | 0.7105 |
| 0.7355        | 5.5   | 201344 | 0.8907          | 0.9646   | 0.7108 |
| 0.7334        | 6.0   | 219648 | 0.8795          | 0.9649   | 0.7124 |
| 0.6991        | 6.5   | 237952 | 0.8772          | 0.9657   | 0.7132 |
| 0.7001        | 7.0   | 256256 | 0.8670          | 0.9662   | 0.7129 |
| 0.674         | 7.5   | 274560 | 0.8667          | 0.9664   | 0.7149 |
| 0.672         | 8.0   | 292864 | 0.8640          | 0.9666   | 0.7152 |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3