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# distilbert-base-uncased_fold_2_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: 1.8941
- F1: 0.7889

## 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   | 294  | 0.6025          | 0.7402 |
| 0.5688        | 2.0   | 588  | 0.5025          | 0.7943 |
| 0.5688        | 3.0   | 882  | 0.6102          | 0.7794 |
| 0.2582        | 4.0   | 1176 | 0.8896          | 0.7835 |
| 0.2582        | 5.0   | 1470 | 1.0392          | 0.7821 |
| 0.1185        | 6.0   | 1764 | 1.0865          | 0.7848 |
| 0.0461        | 7.0   | 2058 | 1.2951          | 0.7686 |
| 0.0461        | 8.0   | 2352 | 1.3348          | 0.7821 |
| 0.0313        | 9.0   | 2646 | 1.4267          | 0.7876 |
| 0.0313        | 10.0  | 2940 | 1.4004          | 0.7957 |
| 0.0142        | 11.0  | 3234 | 1.5501          | 0.7794 |
| 0.0083        | 12.0  | 3528 | 1.5564          | 0.7903 |
| 0.0083        | 13.0  | 3822 | 1.5699          | 0.7876 |
| 0.0067        | 14.0  | 4116 | 1.7725          | 0.7794 |
| 0.0067        | 15.0  | 4410 | 1.7642          | 0.7767 |
| 0.0031        | 16.0  | 4704 | 1.7891          | 0.7848 |
| 0.0031        | 17.0  | 4998 | 1.8528          | 0.7740 |
| 0.0054        | 18.0  | 5292 | 1.8378          | 0.7781 |
| 0.003         | 19.0  | 5586 | 1.8223          | 0.7862 |
| 0.003         | 20.0  | 5880 | 1.7935          | 0.7930 |
| 0.0021        | 21.0  | 6174 | 1.9117          | 0.7808 |
| 0.0021        | 22.0  | 6468 | 1.8891          | 0.7930 |
| 0.0015        | 23.0  | 6762 | 1.9167          | 0.7916 |
| 0.0006        | 24.0  | 7056 | 1.9193          | 0.7862 |
| 0.0006        | 25.0  | 7350 | 1.8941          | 0.7889 |


### 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_2_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\_2\_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: 1.8941
* F1: 0.7889


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