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# distilbert-base-uncased_fold_1_ternary

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: 2.0582
- F1: 0.7326

## 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  | 0.5524          | 0.6755 |
| 0.5648        | 2.0   | 580  | 0.5654          | 0.7124 |
| 0.5648        | 3.0   | 870  | 0.6547          | 0.6896 |
| 0.2712        | 4.0   | 1160 | 0.8916          | 0.7263 |
| 0.2712        | 5.0   | 1450 | 1.1187          | 0.7120 |
| 0.1147        | 6.0   | 1740 | 1.2778          | 0.7114 |
| 0.0476        | 7.0   | 2030 | 1.4441          | 0.7151 |
| 0.0476        | 8.0   | 2320 | 1.5535          | 0.7133 |
| 0.0187        | 9.0   | 2610 | 1.6439          | 0.7212 |
| 0.0187        | 10.0  | 2900 | 1.7261          | 0.7313 |
| 0.0138        | 11.0  | 3190 | 1.6806          | 0.7292 |
| 0.0138        | 12.0  | 3480 | 1.8425          | 0.7111 |
| 0.009         | 13.0  | 3770 | 1.9207          | 0.7213 |
| 0.0045        | 14.0  | 4060 | 1.8900          | 0.7202 |
| 0.0045        | 15.0  | 4350 | 1.9730          | 0.7216 |
| 0.0042        | 16.0  | 4640 | 2.0775          | 0.7041 |
| 0.0042        | 17.0  | 4930 | 2.0514          | 0.7106 |
| 0.0019        | 18.0  | 5220 | 2.0582          | 0.7326 |
| 0.0039        | 19.0  | 5510 | 2.1010          | 0.7081 |
| 0.0039        | 20.0  | 5800 | 2.0487          | 0.7273 |
| 0.0025        | 21.0  | 6090 | 2.0415          | 0.7254 |
| 0.0025        | 22.0  | 6380 | 2.0753          | 0.7157 |
| 0.0017        | 23.0  | 6670 | 2.0554          | 0.7246 |
| 0.0017        | 24.0  | 6960 | 2.0644          | 0.7290 |
| 0.0001        | 25.0  | 7250 | 2.0711          | 0.7310 |


### 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_1_ternary", "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\_1\_ternary
=========================================


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: 2.0582
* F1: 0.7326


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
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