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---
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
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