---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: QA_REDACTION_NOV1_16
  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. -->

# QA_REDACTION_NOV1_16

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0383

## 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: 3
- eval_batch_size: 3
- seed: 42
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.0454        | 1.0   | 1800  | 0.0552          |
| 0.0534        | 2.0   | 3600  | 0.0423          |
| 0.3243        | 3.0   | 5400  | 0.0335          |
| 0.051         | 4.0   | 7200  | 0.0482          |
| 0.033         | 5.0   | 9000  | 0.0260          |
| 0.0378        | 6.0   | 10800 | 0.0233          |
| 0.0206        | 7.0   | 12600 | 0.0282          |
| 0.0399        | 8.0   | 14400 | 0.0490          |
| 0.009         | 9.0   | 16200 | 0.0282          |
| 0.0239        | 10.0  | 18000 | 0.0383          |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1
- Datasets 2.14.6
- Tokenizers 0.14.1