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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-mul-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-mul-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: 0.7376 |
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- Precision: 0.0 |
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- Recall: 0.0 |
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- F1: 0 |
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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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| 0.3037 | 0.45 | 500 | 0.4545 | 0.0 | 0.0 | 0 | |
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| 0.2008 | 0.91 | 1000 | 0.4427 | 0.0 | 0.0 | 0 | |
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| 0.1567 | 1.36 | 1500 | 0.5872 | 0.0 | 0.0 | 0 | |
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| 0.1402 | 1.82 | 2000 | 0.6592 | 0.0 | 0.0 | 0 | |
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| 0.1218 | 2.27 | 2500 | 0.7135 | 0.0 | 0.0 | 0 | |
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| 0.1104 | 2.72 | 3000 | 0.7376 | 0.0 | 0.0 | 0 | |
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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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