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--- |
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license: mit |
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base_model: xlm-roberta-base |
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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: finetuned_roberta-base |
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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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# finetuned_roberta-base |
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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: 1.2574 |
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- Accuracy: 0.6033 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 15 |
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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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| 1.48 | 1.0 | 75 | 1.4001 | 0.41 | |
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| 1.2847 | 2.0 | 150 | 1.1993 | 0.58 | |
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| 1.1522 | 3.0 | 225 | 1.0007 | 0.6333 | |
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| 0.9921 | 4.0 | 300 | 0.9189 | 0.66 | |
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| 0.9104 | 5.0 | 375 | 0.8855 | 0.69 | |
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| 0.8371 | 6.0 | 450 | 0.9431 | 0.6767 | |
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| 0.699 | 7.0 | 525 | 0.9500 | 0.6633 | |
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| 0.6872 | 8.0 | 600 | 0.9728 | 0.7033 | |
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| 0.5867 | 9.0 | 675 | 0.9939 | 0.6867 | |
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| 0.5323 | 10.0 | 750 | 1.1115 | 0.69 | |
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| 0.4066 | 11.0 | 825 | 1.2031 | 0.6667 | |
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| 0.3517 | 12.0 | 900 | 1.2193 | 0.65 | |
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| 0.3114 | 13.0 | 975 | 1.2281 | 0.67 | |
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| 0.3102 | 14.0 | 1050 | 1.2691 | 0.67 | |
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| 0.2681 | 15.0 | 1125 | 1.2818 | 0.6633 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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