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# distilbert-base-uncased_fold_6_binary_v1

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7209
- F1: 0.8156

## 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: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 290  | 0.4115          | 0.8048 |
| 0.3976        | 2.0   | 580  | 0.3980          | 0.8156 |
| 0.3976        | 3.0   | 870  | 0.5953          | 0.8142 |
| 0.1965        | 4.0   | 1160 | 0.7940          | 0.8057 |
| 0.1965        | 5.0   | 1450 | 0.8098          | 0.8069 |
| 0.0847        | 6.0   | 1740 | 1.0293          | 0.7913 |
| 0.03          | 7.0   | 2030 | 1.1649          | 0.8073 |
| 0.03          | 8.0   | 2320 | 1.2876          | 0.7973 |
| 0.0166        | 9.0   | 2610 | 1.3260          | 0.8038 |
| 0.0166        | 10.0  | 2900 | 1.3523          | 0.8084 |
| 0.0062        | 11.0  | 3190 | 1.3814          | 0.8097 |
| 0.0062        | 12.0  | 3480 | 1.4134          | 0.8165 |
| 0.0113        | 13.0  | 3770 | 1.5374          | 0.8068 |
| 0.006         | 14.0  | 4060 | 1.5808          | 0.8100 |
| 0.006         | 15.0  | 4350 | 1.6551          | 0.7972 |
| 0.0088        | 16.0  | 4640 | 1.5793          | 0.8116 |
| 0.0088        | 17.0  | 4930 | 1.6134          | 0.8143 |
| 0.0021        | 18.0  | 5220 | 1.6204          | 0.8119 |
| 0.0031        | 19.0  | 5510 | 1.7006          | 0.8029 |
| 0.0031        | 20.0  | 5800 | 1.6777          | 0.8145 |
| 0.0019        | 21.0  | 6090 | 1.7202          | 0.8079 |
| 0.0019        | 22.0  | 6380 | 1.7539          | 0.8053 |
| 0.0008        | 23.0  | 6670 | 1.7408          | 0.8119 |
| 0.0008        | 24.0  | 6960 | 1.7388          | 0.8176 |
| 0.0014        | 25.0  | 7250 | 1.7209          | 0.8156 |


### Framework versions

- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "distilbert-base-uncased_fold_6_binary_v1", "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 

distilbert-base-uncased\_fold\_6\_binary\_v1
============================================


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


* Loss: 1.7209
* F1: 0.8156


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: 25


### Training results



### Framework versions


* Transformers 4.21.0
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1



### 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: 25 ### Training results ### Framework versions


* Transformers 4.21.0
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
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: 25 ### Training results ### Framework versions


* Transformers 4.21.0
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
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: 25### Training results### Framework versions


* Transformers 4.21.0
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1