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# distilbert-base-uncased_fold_9_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: 1.9406
- F1: 0.7841

## 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   | 292  | 0.5684          | 0.7635 |
| 0.5656        | 2.0   | 584  | 0.5753          | 0.7725 |
| 0.5656        | 3.0   | 876  | 0.6159          | 0.7866 |
| 0.2499        | 4.0   | 1168 | 0.7743          | 0.7828 |
| 0.2499        | 5.0   | 1460 | 0.9820          | 0.7674 |
| 0.1153        | 6.0   | 1752 | 1.2383          | 0.7738 |
| 0.0547        | 7.0   | 2044 | 1.2468          | 0.7815 |
| 0.0547        | 8.0   | 2336 | 1.3480          | 0.7622 |
| 0.0233        | 9.0   | 2628 | 1.3791          | 0.7892 |
| 0.0233        | 10.0  | 2920 | 1.4344          | 0.7841 |
| 0.0142        | 11.0  | 3212 | 1.4958          | 0.7802 |
| 0.0087        | 12.0  | 3504 | 1.5714          | 0.7674 |
| 0.0087        | 13.0  | 3796 | 1.6129          | 0.7956 |
| 0.0111        | 14.0  | 4088 | 1.7799          | 0.7751 |
| 0.0111        | 15.0  | 4380 | 1.7272          | 0.7789 |
| 0.0055        | 16.0  | 4672 | 1.7696          | 0.7866 |
| 0.0055        | 17.0  | 4964 | 1.8622          | 0.7789 |
| 0.003         | 18.0  | 5256 | 1.8563          | 0.7802 |
| 0.0004        | 19.0  | 5548 | 1.8993          | 0.7815 |
| 0.0004        | 20.0  | 5840 | 1.9199          | 0.7853 |
| 0.0005        | 21.0  | 6132 | 1.9003          | 0.7879 |
| 0.0005        | 22.0  | 6424 | 1.9161          | 0.7828 |
| 0.0011        | 23.0  | 6716 | 1.9691          | 0.7815 |
| 0.0017        | 24.0  | 7008 | 1.9492          | 0.7841 |
| 0.0017        | 25.0  | 7300 | 1.9406          | 0.7841 |


### 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_9_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\_9\_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: 1.9406
* F1: 0.7841


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