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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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datasets: |
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- arcd |
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model-index: |
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- name: rinna-roberta-qa-ar2 |
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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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# rinna-roberta-qa-ar2 |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the arcd dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 7.3167 |
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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: 7e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 32 |
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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_steps: 100 |
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- num_epochs: 170 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.3148 | 6.86 | 150 | 4.5451 | |
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| 0.2021 | 13.71 | 300 | 4.3560 | |
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| 0.1134 | 20.57 | 450 | 5.1730 | |
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| 0.0648 | 27.43 | 600 | 5.0504 | |
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| 0.0734 | 34.29 | 750 | 5.3601 | |
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| 0.032 | 41.14 | 900 | 5.4291 | |
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| 0.0171 | 48.0 | 1050 | 6.9606 | |
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| 0.0343 | 54.86 | 1200 | 4.9076 | |
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| 0.0186 | 61.71 | 1350 | 6.7967 | |
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| 0.0054 | 68.57 | 1500 | 6.0515 | |
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| 0.0118 | 75.43 | 1650 | 7.0908 | |
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| 0.0027 | 82.29 | 1800 | 7.5651 | |
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| 0.0078 | 89.14 | 1950 | 7.3787 | |
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| 0.0172 | 96.0 | 2100 | 7.7559 | |
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| 0.0077 | 102.86 | 2250 | 7.1376 | |
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| 0.0041 | 109.71 | 2400 | 7.3236 | |
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| 0.0022 | 116.57 | 2550 | 7.3134 | |
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| 0.0004 | 123.43 | 2700 | 7.2484 | |
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| 0.0018 | 130.29 | 2850 | 7.1747 | |
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| 0.0009 | 137.14 | 3000 | 7.4311 | |
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| 0.0008 | 144.0 | 3150 | 7.5083 | |
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| 0.0006 | 150.86 | 3300 | 7.4622 | |
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| 0.0002 | 157.71 | 3450 | 7.3167 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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