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# distilbert-base-uncased_fold_10_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: 1.6912
- F1: 0.7977

## 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   | 288  | 0.4002          | 0.8012 |
| 0.4056        | 2.0   | 576  | 0.4372          | 0.8075 |
| 0.4056        | 3.0   | 864  | 0.4720          | 0.8071 |
| 0.1958        | 4.0   | 1152 | 0.8156          | 0.7980 |
| 0.1958        | 5.0   | 1440 | 0.8633          | 0.8055 |
| 0.0847        | 6.0   | 1728 | 0.9761          | 0.8041 |
| 0.0356        | 7.0   | 2016 | 1.1816          | 0.7861 |
| 0.0356        | 8.0   | 2304 | 1.2251          | 0.7918 |
| 0.0215        | 9.0   | 2592 | 1.3423          | 0.7798 |
| 0.0215        | 10.0  | 2880 | 1.3888          | 0.7913 |
| 0.013         | 11.0  | 3168 | 1.2899          | 0.8040 |
| 0.013         | 12.0  | 3456 | 1.4247          | 0.8051 |
| 0.0049        | 13.0  | 3744 | 1.5436          | 0.7991 |
| 0.0061        | 14.0  | 4032 | 1.5762          | 0.7991 |
| 0.0061        | 15.0  | 4320 | 1.5461          | 0.7998 |
| 0.0054        | 16.0  | 4608 | 1.5622          | 0.8018 |
| 0.0054        | 17.0  | 4896 | 1.6658          | 0.7991 |
| 0.0021        | 18.0  | 5184 | 1.6765          | 0.7972 |
| 0.0021        | 19.0  | 5472 | 1.6864          | 0.7973 |
| 0.0052        | 20.0  | 5760 | 1.6303          | 0.8030 |
| 0.0029        | 21.0  | 6048 | 1.6631          | 0.7947 |
| 0.0029        | 22.0  | 6336 | 1.6571          | 0.8006 |
| 0.0027        | 23.0  | 6624 | 1.6729          | 0.7949 |
| 0.0027        | 24.0  | 6912 | 1.6931          | 0.7934 |
| 0.0001        | 25.0  | 7200 | 1.6912          | 0.7977 |


### 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_10_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\_10\_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: 1.6912
* F1: 0.7977


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