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# 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

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["arcd"], "model-index": [{"name": "rinna-roberta-qa-ar2", "results": []}]}
transformers pytorch tensorboard xlm-roberta question-answering generated_from_trainer dataset:arcd license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #question-answering #generated_from_trainer #dataset-arcd #license-mit #endpoints_compatible #region-us 

rinna-roberta-qa-ar2
====================


This model is a fine-tuned version of 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



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### 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 ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #question-answering #generated_from_trainer #dataset-arcd #license-mit #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3