
<!-- 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. -->

# my_awesome_model_4

This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0866
- Accuracy: 0.9644

## 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: 2e-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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.09  | 200  | 0.2342          | 0.9098   |
| No log        | 0.19  | 400  | 0.2575          | 0.9178   |
| 0.2768        | 0.28  | 600  | 0.1922          | 0.9316   |
| 0.2768        | 0.38  | 800  | 0.1274          | 0.9566   |
| 0.1402        | 0.47  | 1000 | 0.1153          | 0.9566   |
| 0.1402        | 0.57  | 1200 | 0.1516          | 0.9472   |
| 0.1402        | 0.66  | 1400 | 0.0866          | 0.9644   |
| 0.126         | 0.75  | 1600 | 0.1375          | 0.9572   |
| 0.126         | 0.85  | 1800 | 0.1084          | 0.9638   |
| 0.1068        | 0.94  | 2000 | 0.0998          | 0.9655   |
| 0.1068        | 1.04  | 2200 | 0.1060          | 0.9656   |
| 0.1068        | 1.13  | 2400 | 0.0999          | 0.9689   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "my_awesome_model_4", "results": []}]}
transformers pytorch tensorboard distilbert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

my\_awesome\_model\_4
=====================


This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0866
* Accuracy: 0.9644


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: 2e-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: 2


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 2 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #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: 2e-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: 2 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2