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# distilbert-base-uncased_fold_3_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: 1.8908
- F1: 0.7879

## 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  | 0.5873          | 0.7636 |
| 0.5479        | 2.0   | 578  | 0.5788          | 0.7697 |
| 0.5479        | 3.0   | 867  | 0.6286          | 0.7770 |
| 0.2412        | 4.0   | 1156 | 0.8845          | 0.7661 |
| 0.2412        | 5.0   | 1445 | 0.9894          | 0.7818 |
| 0.1191        | 6.0   | 1734 | 1.0856          | 0.7842 |
| 0.0543        | 7.0   | 2023 | 1.2852          | 0.7830 |
| 0.0543        | 8.0   | 2312 | 1.4295          | 0.7673 |
| 0.0223        | 9.0   | 2601 | 1.4716          | 0.7806 |
| 0.0223        | 10.0  | 2890 | 1.6007          | 0.7636 |
| 0.0122        | 11.0  | 3179 | 1.6744          | 0.7673 |
| 0.0122        | 12.0  | 3468 | 1.6954          | 0.7685 |
| 0.0129        | 13.0  | 3757 | 1.7273          | 0.7733 |
| 0.0057        | 14.0  | 4046 | 1.7114          | 0.7758 |
| 0.0057        | 15.0  | 4335 | 1.7480          | 0.7733 |
| 0.0045        | 16.0  | 4624 | 1.8322          | 0.7830 |
| 0.0045        | 17.0  | 4913 | 1.7448          | 0.7830 |
| 0.0047        | 18.0  | 5202 | 1.8126          | 0.7782 |
| 0.0047        | 19.0  | 5491 | 1.9021          | 0.7673 |
| 0.0018        | 20.0  | 5780 | 1.9011          | 0.7830 |
| 0.0026        | 21.0  | 6069 | 1.8771          | 0.7806 |
| 0.0026        | 22.0  | 6358 | 1.8634          | 0.7806 |
| 0.0012        | 23.0  | 6647 | 1.8926          | 0.7830 |
| 0.0012        | 24.0  | 6936 | 1.8922          | 0.7855 |
| 0.0005        | 25.0  | 7225 | 1.8908          | 0.7879 |


### 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_3_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\_3\_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: 1.8908
* F1: 0.7879


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