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---
library_name: transformers
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: mtl-xlmr-base-viwiki-v3
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. -->
# mtl-xlmr-base-viwiki-v3
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: 0.6780
## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8769 | 1.0 | 960 | 0.7713 |
| 0.5802 | 2.0 | 1920 | 0.6602 |
| 0.7036 | 3.0 | 2880 | 0.6153 |
| 0.4554 | 4.0 | 3840 | 0.6017 |
| 0.3767 | 5.0 | 4800 | 0.6026 |
| 0.3122 | 6.0 | 5760 | 0.6543 |
| 0.2951 | 7.0 | 6720 | 0.6342 |
| 0.2424 | 8.0 | 7680 | 0.6403 |
| 0.3225 | 9.0 | 8640 | 0.6522 |
| 0.2981 | 10.0 | 9600 | 0.6780 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.2.1
- Datasets 2.21.0
- Tokenizers 0.19.1
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