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# roberta-similarity

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5172
- Accuracy: 0.834

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6747        | 0.16  | 10   | 0.6562          | 0.672    |
| 0.5355        | 0.32  | 20   | 0.5163          | 0.772    |
| 0.5374        | 0.48  | 30   | 0.5901          | 0.74     |
| 0.5064        | 0.63  | 40   | 0.4904          | 0.782    |
| 0.4241        | 0.79  | 50   | 0.5793          | 0.73     |
| 0.5484        | 0.95  | 60   | 0.5381          | 0.776    |
| 0.5441        | 1.11  | 70   | 0.5375          | 0.764    |
| 0.445         | 1.27  | 80   | 0.5096          | 0.792    |
| 0.4436        | 1.43  | 90   | 0.5617          | 0.814    |
| 0.4677        | 1.59  | 100  | 0.6145          | 0.796    |
| 0.4306        | 1.75  | 110  | 0.6105          | 0.814    |
| 0.3197        | 1.9   | 120  | 0.5112          | 0.772    |
| 0.3373        | 2.06  | 130  | 0.5168          | 0.818    |
| 0.3128        | 2.22  | 140  | 0.5007          | 0.824    |
| 0.3286        | 2.38  | 150  | 0.4900          | 0.83     |
| 0.476         | 2.54  | 160  | 0.4989          | 0.79     |
| 0.413         | 2.7   | 170  | 0.6129          | 0.748    |
| 0.3811        | 2.86  | 180  | 0.5137          | 0.818    |
| 0.3224        | 3.02  | 190  | 0.5178          | 0.806    |
| 0.2917        | 3.17  | 200  | 0.5382          | 0.802    |
| 0.3696        | 3.33  | 210  | 0.5610          | 0.822    |
| 0.3019        | 3.49  | 220  | 0.7040          | 0.792    |
| 0.3354        | 3.65  | 230  | 0.5342          | 0.826    |
| 0.2854        | 3.81  | 240  | 0.5047          | 0.832    |
| 0.3079        | 3.97  | 250  | 0.5124          | 0.83     |
| 0.3271        | 4.13  | 260  | 0.5876          | 0.808    |
| 0.276         | 4.29  | 270  | 0.5271          | 0.824    |
| 0.2519        | 4.44  | 280  | 0.5309          | 0.832    |
| 0.2107        | 4.6   | 290  | 0.5186          | 0.834    |
| 0.2471        | 4.76  | 300  | 0.5191          | 0.838    |
| 0.2751        | 4.92  | 310  | 0.5172          | 0.834    |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "roberta-similarity", "results": []}]}
transformers pytorch roberta text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

roberta-similarity
==================


This model is a fine-tuned version of roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.5172
* Accuracy: 0.834


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: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Tokenizers 0.13.3