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---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: xlm-ate-nobi-mul-nes
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. -->
# xlm-ate-nobi-mul-nes
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: 0.7376
- Precision: 0.0
- Recall: 0.0
- F1: 0
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--:|
| 0.3037 | 0.45 | 500 | 0.4545 | 0.0 | 0.0 | 0 |
| 0.2008 | 0.91 | 1000 | 0.4427 | 0.0 | 0.0 | 0 |
| 0.1567 | 1.36 | 1500 | 0.5872 | 0.0 | 0.0 | 0 |
| 0.1402 | 1.82 | 2000 | 0.6592 | 0.0 | 0.0 | 0 |
| 0.1218 | 2.27 | 2500 | 0.7135 | 0.0 | 0.0 | 0 |
| 0.1104 | 2.72 | 3000 | 0.7376 | 0.0 | 0.0 | 0 |
### Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2
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