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# distilbert-base-uncased_fold_11_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: 1.8389
- F1: 0.8057

## 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  | 0.4534          | 0.8011 |
| 0.4027        | 2.0   | 576  | 0.4299          | 0.8121 |
| 0.4027        | 3.0   | 864  | 0.4840          | 0.8142 |
| 0.1947        | 4.0   | 1152 | 0.7501          | 0.7992 |
| 0.1947        | 5.0   | 1440 | 1.0307          | 0.7866 |
| 0.0771        | 6.0   | 1728 | 1.1292          | 0.8034 |
| 0.0253        | 7.0   | 2016 | 1.2620          | 0.8033 |
| 0.0253        | 8.0   | 2304 | 1.4065          | 0.7954 |
| 0.0137        | 9.0   | 2592 | 1.4922          | 0.7887 |
| 0.0137        | 10.0  | 2880 | 1.4922          | 0.8050 |
| 0.0046        | 11.0  | 3168 | 1.4883          | 0.8097 |
| 0.0046        | 12.0  | 3456 | 1.5542          | 0.8133 |
| 0.0066        | 13.0  | 3744 | 1.5180          | 0.8000 |
| 0.0094        | 14.0  | 4032 | 1.6762          | 0.7919 |
| 0.0094        | 15.0  | 4320 | 1.5808          | 0.8005 |
| 0.0047        | 16.0  | 4608 | 1.7025          | 0.8012 |
| 0.0047        | 17.0  | 4896 | 1.6494          | 0.7986 |
| 0.0039        | 18.0  | 5184 | 1.7218          | 0.8010 |
| 0.0039        | 19.0  | 5472 | 1.8293          | 0.7994 |
| 0.0005        | 20.0  | 5760 | 1.8142          | 0.7980 |
| 0.0033        | 21.0  | 6048 | 1.8350          | 0.8037 |
| 0.0033        | 22.0  | 6336 | 1.8361          | 0.8042 |
| 0.0023        | 23.0  | 6624 | 1.8715          | 0.7996 |
| 0.0023        | 24.0  | 6912 | 1.8411          | 0.8057 |
| 0.0019        | 25.0  | 7200 | 1.8389          | 0.8057 |


### 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_11_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\_11\_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: 1.8389
* F1: 0.8057


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
passage: 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