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# distilbert-base-uncased_fold_4_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: 1.2977
- F1: 0.8083

## 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   | 289  | 0.3701          | 0.7903 |
| 0.4005        | 2.0   | 578  | 0.3669          | 0.7994 |
| 0.4005        | 3.0   | 867  | 0.5038          | 0.7955 |
| 0.1945        | 4.0   | 1156 | 0.6353          | 0.8006 |
| 0.1945        | 5.0   | 1445 | 0.8974          | 0.7826 |
| 0.0909        | 6.0   | 1734 | 0.8533          | 0.7764 |
| 0.0389        | 7.0   | 2023 | 0.9969          | 0.7957 |
| 0.0389        | 8.0   | 2312 | 1.0356          | 0.7952 |
| 0.0231        | 9.0   | 2601 | 1.1538          | 0.7963 |
| 0.0231        | 10.0  | 2890 | 1.2011          | 0.7968 |
| 0.0051        | 11.0  | 3179 | 1.2329          | 0.7935 |
| 0.0051        | 12.0  | 3468 | 1.2829          | 0.8056 |
| 0.0066        | 13.0  | 3757 | 1.2946          | 0.7956 |
| 0.004         | 14.0  | 4046 | 1.2977          | 0.8083 |
| 0.004         | 15.0  | 4335 | 1.3970          | 0.7957 |
| 0.0007        | 16.0  | 4624 | 1.3361          | 0.7917 |
| 0.0007        | 17.0  | 4913 | 1.5782          | 0.7954 |
| 0.0107        | 18.0  | 5202 | 1.4641          | 0.7900 |
| 0.0107        | 19.0  | 5491 | 1.4490          | 0.7957 |
| 0.0058        | 20.0  | 5780 | 1.4607          | 0.7932 |
| 0.0016        | 21.0  | 6069 | 1.5048          | 0.7939 |
| 0.0016        | 22.0  | 6358 | 1.5219          | 0.7945 |
| 0.0027        | 23.0  | 6647 | 1.4783          | 0.7937 |
| 0.0027        | 24.0  | 6936 | 1.4715          | 0.7981 |
| 0.0004        | 25.0  | 7225 | 1.4989          | 0.7900 |


### 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_4_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\_4\_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: 1.2977
* F1: 0.8083


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