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# commitC

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3178
- Accuracy: 0.6939

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 32   | 0.9701          | 0.5545   |
| No log        | 2.0   | 64   | 0.8482          | 0.5970   |
| No log        | 3.0   | 96   | 0.7623          | 0.6606   |
| No log        | 4.0   | 128  | 0.7500          | 0.6818   |
| No log        | 5.0   | 160  | 0.7741          | 0.7      |
| No log        | 6.0   | 192  | 0.8143          | 0.7030   |
| No log        | 7.0   | 224  | 0.9409          | 0.6909   |
| No log        | 8.0   | 256  | 1.0390          | 0.6939   |
| No log        | 9.0   | 288  | 1.1710          | 0.6909   |
| No log        | 10.0  | 320  | 1.1657          | 0.6970   |
| No log        | 11.0  | 352  | 1.1804          | 0.6939   |
| No log        | 12.0  | 384  | 1.2182          | 0.6970   |
| No log        | 13.0  | 416  | 1.1840          | 0.7091   |
| No log        | 14.0  | 448  | 1.3097          | 0.7030   |
| No log        | 15.0  | 480  | 1.2168          | 0.7242   |
| 0.2806        | 16.0  | 512  | 1.2970          | 0.7      |
| 0.2806        | 17.0  | 544  | 1.3139          | 0.7      |
| 0.2806        | 18.0  | 576  | 1.3116          | 0.6939   |
| 0.2806        | 19.0  | 608  | 1.3045          | 0.6970   |
| 0.2806        | 20.0  | 640  | 1.3178          | 0.6939   |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "commitC", "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 

commitC
=======


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


* Loss: 1.3178
* Accuracy: 0.6939


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: 20


### 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: 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: 20 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* 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: 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: 20 ### Training results ### Framework versions


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