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# distil-s

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6895
- Rmse: 0.8304
- Mse: 0.6895
- Mae: 0.5893

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rmse   | Mse    | Mae    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 0.6982        | 1.0   | 492  | 0.6440          | 0.8025 | 0.6440 | 0.5841 |
| 0.5922        | 2.0   | 984  | 0.6412          | 0.8007 | 0.6412 | 0.5837 |
| 0.5873        | 3.0   | 1476 | 0.6101          | 0.7811 | 0.6101 | 0.6029 |
| 0.5888        | 4.0   | 1968 | 0.6272          | 0.7920 | 0.6272 | 0.5834 |
| 0.5852        | 5.0   | 2460 | 0.6071          | 0.7791 | 0.6071 | 0.6181 |
| 0.5817        | 6.0   | 2952 | 0.6023          | 0.7761 | 0.6023 | 0.5949 |
| 0.571         | 7.0   | 3444 | 0.6895          | 0.8304 | 0.6895 | 0.5893 |


### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "distil-s", "results": []}]}
transformers pytorch roberta text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

distil-s
========


This model is a fine-tuned version of distilroberta-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.6895
* Rmse: 0.8304
* Mse: 0.6895
* Mae: 0.5893


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: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.9.0+cu111
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.9.0+cu111
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.9.0+cu111
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.9.0+cu111
* Datasets 2.4.0
* Tokenizers 0.12.1