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---
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license:
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---
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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model-index:
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- name: xlm-ate-nobi-en-nes
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# xlm-ate-nobi-en-nes
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2581
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- Precision: 0.5875
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- Recall: 0.4794
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- F1: 0.5280
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 20
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
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| 0.2205 | 1.85 | 500 | 0.5622 | 0.5705 | 0.4546 | 0.5060 |
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| 0.077 | 3.69 | 1000 | 0.7307 | 0.5715 | 0.4819 | 0.5229 |
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| 0.0421 | 5.54 | 1500 | 0.8561 | 0.5725 | 0.4965 | 0.5318 |
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| 0.0253 | 7.38 | 2000 | 0.8979 | 0.5601 | 0.5181 | 0.5383 |
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| 0.0157 | 9.23 | 2500 | 1.1252 | 0.6047 | 0.4565 | 0.5203 |
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| 0.0099 | 11.07 | 3000 | 1.1651 | 0.5874 | 0.4781 | 0.5271 |
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| 0.0077 | 12.92 | 3500 | 1.0574 | 0.5471 | 0.5270 | 0.5369 |
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| 0.0052 | 14.76 | 4000 | 1.1903 | 0.5879 | 0.4863 | 0.5323 |
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| 0.0034 | 16.61 | 4500 | 1.2581 | 0.5875 | 0.4794 | 0.5280 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 2.0.1+cu117
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- Datasets 2.9.0
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- Tokenizers 0.13.2
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