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README.md
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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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- accuracy
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model-index:
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- name: test-results-concat
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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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# test-results-concat
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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: 0.9408
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- Accuracy: 0.6012
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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: 8
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- eval_batch_size: 8
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- seed: 123
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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: 3
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 1.0408 | 0.33 | 5000 | 0.9773 | 0.5697 |
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| 0.9442 | 0.67 | 10000 | 0.9701 | 0.5853 |
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| 0.9579 | 1.0 | 15000 | 0.9502 | 0.5895 |
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| 0.8867 | 1.33 | 20000 | 0.9467 | 0.5897 |
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| 0.8819 | 1.67 | 25000 | 0.9371 | 0.5893 |
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| 0.8748 | 2.0 | 30000 | 0.9408 | 0.6012 |
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| 0.7759 | 2.33 | 35000 | 0.9734 | 0.5968 |
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| 0.7599 | 2.67 | 40000 | 0.9722 | 0.5948 |
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| 0.7626 | 3.0 | 45000 | 0.9654 | 0.5975 |
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### Framework versions
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- Transformers 4.23.1
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- Pytorch 1.12.1+cu113
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- Datasets 2.6.1
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- Tokenizers 0.13.1
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