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---
license: mit
tags:
- generated_from_trainer
datasets:
- arcd
model-index:
- name: rinna-roberta-qa-ar2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# rinna-roberta-qa-ar2
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the arcd dataset.
It achieves the following results on the evaluation set:
- Loss: 7.3167
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 7e-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 170
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.3148 | 6.86 | 150 | 4.5451 |
| 0.2021 | 13.71 | 300 | 4.3560 |
| 0.1134 | 20.57 | 450 | 5.1730 |
| 0.0648 | 27.43 | 600 | 5.0504 |
| 0.0734 | 34.29 | 750 | 5.3601 |
| 0.032 | 41.14 | 900 | 5.4291 |
| 0.0171 | 48.0 | 1050 | 6.9606 |
| 0.0343 | 54.86 | 1200 | 4.9076 |
| 0.0186 | 61.71 | 1350 | 6.7967 |
| 0.0054 | 68.57 | 1500 | 6.0515 |
| 0.0118 | 75.43 | 1650 | 7.0908 |
| 0.0027 | 82.29 | 1800 | 7.5651 |
| 0.0078 | 89.14 | 1950 | 7.3787 |
| 0.0172 | 96.0 | 2100 | 7.7559 |
| 0.0077 | 102.86 | 2250 | 7.1376 |
| 0.0041 | 109.71 | 2400 | 7.3236 |
| 0.0022 | 116.57 | 2550 | 7.3134 |
| 0.0004 | 123.43 | 2700 | 7.2484 |
| 0.0018 | 130.29 | 2850 | 7.1747 |
| 0.0009 | 137.14 | 3000 | 7.4311 |
| 0.0008 | 144.0 | 3150 | 7.5083 |
| 0.0006 | 150.86 | 3300 | 7.4622 |
| 0.0002 | 157.71 | 3450 | 7.3167 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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