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# distilbert-base-uncased_fold_5_binary

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: 0.5093
- F1: 0.7801

## 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  | 0.4760          | 0.7315 |
| 0.3992        | 2.0   | 576  | 0.4428          | 0.7785 |
| 0.3992        | 3.0   | 864  | 0.5093          | 0.7801 |
| 0.2021        | 4.0   | 1152 | 0.6588          | 0.7634 |
| 0.2021        | 5.0   | 1440 | 0.9174          | 0.7713 |
| 0.0945        | 6.0   | 1728 | 0.9832          | 0.7726 |
| 0.0321        | 7.0   | 2016 | 1.2103          | 0.7672 |
| 0.0321        | 8.0   | 2304 | 1.3759          | 0.7616 |
| 0.0134        | 9.0   | 2592 | 1.4405          | 0.7570 |
| 0.0134        | 10.0  | 2880 | 1.4591          | 0.7710 |
| 0.0117        | 11.0  | 3168 | 1.4947          | 0.7713 |
| 0.0117        | 12.0  | 3456 | 1.6224          | 0.7419 |
| 0.0081        | 13.0  | 3744 | 1.6462          | 0.7520 |
| 0.0083        | 14.0  | 4032 | 1.6880          | 0.7637 |
| 0.0083        | 15.0  | 4320 | 1.7080          | 0.7380 |
| 0.0048        | 16.0  | 4608 | 1.7352          | 0.7551 |
| 0.0048        | 17.0  | 4896 | 1.6761          | 0.7713 |
| 0.0024        | 18.0  | 5184 | 1.7553          | 0.76   |
| 0.0024        | 19.0  | 5472 | 1.7312          | 0.7673 |
| 0.005         | 20.0  | 5760 | 1.7334          | 0.7713 |
| 0.0032        | 21.0  | 6048 | 1.7963          | 0.7578 |
| 0.0032        | 22.0  | 6336 | 1.7529          | 0.7679 |
| 0.0025        | 23.0  | 6624 | 1.7741          | 0.7662 |
| 0.0025        | 24.0  | 6912 | 1.7515          | 0.7679 |
| 0.0004        | 25.0  | 7200 | 1.7370          | 0.7765 |


### 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_5_binary", "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\_5\_binary
========================================


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: 0.5093
* F1: 0.7801


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