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# distilbert-base-uncased_fold_10_ternary_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: 1.9887
- F1: 0.7797

## 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  | 0.5701          | 0.7463 |
| 0.5651        | 2.0   | 580  | 0.5359          | 0.7748 |
| 0.5651        | 3.0   | 870  | 0.6043          | 0.7847 |
| 0.2605        | 4.0   | 1160 | 1.0124          | 0.7587 |
| 0.2605        | 5.0   | 1450 | 1.1140          | 0.7599 |
| 0.1223        | 6.0   | 1740 | 1.2713          | 0.7859 |
| 0.0469        | 7.0   | 2030 | 1.3188          | 0.7822 |
| 0.0469        | 8.0   | 2320 | 1.3819          | 0.7946 |
| 0.0279        | 9.0   | 2610 | 1.5444          | 0.7847 |
| 0.0279        | 10.0  | 2900 | 1.5851          | 0.7908 |
| 0.0084        | 11.0  | 3190 | 1.7003          | 0.7822 |
| 0.0084        | 12.0  | 3480 | 1.8148          | 0.7748 |
| 0.007         | 13.0  | 3770 | 1.7651          | 0.7748 |
| 0.008         | 14.0  | 4060 | 1.8423          | 0.7748 |
| 0.008         | 15.0  | 4350 | 1.7871          | 0.7809 |
| 0.0054        | 16.0  | 4640 | 1.9324          | 0.7748 |
| 0.0054        | 17.0  | 4930 | 1.8685          | 0.7809 |
| 0.0048        | 18.0  | 5220 | 1.9901          | 0.7797 |
| 0.002         | 19.0  | 5510 | 1.9273          | 0.7785 |
| 0.002         | 20.0  | 5800 | 1.9945          | 0.7809 |
| 0.0018        | 21.0  | 6090 | 1.9250          | 0.7785 |
| 0.0018        | 22.0  | 6380 | 1.9929          | 0.7822 |
| 0.0032        | 23.0  | 6670 | 1.9306          | 0.7859 |
| 0.0032        | 24.0  | 6960 | 1.9603          | 0.7847 |
| 0.0029        | 25.0  | 7250 | 1.9887          | 0.7797 |


### 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_ternary_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\_ternary\_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: 1.9887
* F1: 0.7797


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