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# distilbert-base-cased-reward-neurallinguisticpioneers

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2411
- Mse: 3.7748

## 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: constant
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.4559        | 1.0   | 122  | 0.6534          | 3.4024 |
| 0.5476        | 2.0   | 244  | 0.5601          | 3.8827 |
| 0.4224        | 3.0   | 366  | 0.4717          | 3.8263 |
| 0.3534        | 4.0   | 488  | 0.3511          | 3.7530 |
| 0.2827        | 5.0   | 610  | 0.2960          | 3.8889 |
| 0.2541        | 6.0   | 732  | 0.2416          | 3.5817 |
| 0.2289        | 7.0   | 854  | 0.3085          | 4.0660 |
| 0.1997        | 8.0   | 976  | 0.3212          | 3.4440 |
| 0.1889        | 9.0   | 1098 | 0.2852          | 3.9351 |
| 0.1752        | 10.0  | 1220 | 0.2360          | 3.8505 |
| 0.1683        | 11.0  | 1342 | 0.2939          | 4.1039 |
| 0.1601        | 12.0  | 1464 | 0.3242          | 4.0499 |
| 0.155         | 13.0  | 1586 | 0.2297          | 3.8442 |
| 0.1478        | 14.0  | 1708 | 0.2707          | 3.8680 |
| 0.1439        | 15.0  | 1830 | 0.2582          | 3.8703 |
| 0.1462        | 16.0  | 1952 | 0.2411          | 3.7748 |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.0+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "distilbert-base-cased-reward-neurallinguisticpioneers", "results": []}]}
transformers pytorch distilbert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

distilbert-base-cased-reward-neurallinguisticpioneers
=====================================================


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


* Loss: 0.2411
* Mse: 3.7748


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: constant
* num\_epochs: 30


### Training results



### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### 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: constant
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #distilbert #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: constant
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3