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# distilbert-base-uncased_fold_4_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: 1.2981
- F1: 0.7565

## 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  | 0.5588          | 0.6984 |
| 0.5547        | 2.0   | 578  | 0.5283          | 0.7336 |
| 0.5547        | 3.0   | 867  | 0.7038          | 0.7202 |
| 0.2479        | 4.0   | 1156 | 0.8949          | 0.7284 |
| 0.2479        | 5.0   | 1445 | 0.9959          | 0.7286 |
| 0.1181        | 6.0   | 1734 | 1.0663          | 0.7311 |
| 0.0508        | 7.0   | 2023 | 1.2377          | 0.7054 |
| 0.0508        | 8.0   | 2312 | 1.2981          | 0.7565 |
| 0.0185        | 9.0   | 2601 | 1.3532          | 0.7407 |
| 0.0185        | 10.0  | 2890 | 1.5365          | 0.7333 |
| 0.0103        | 11.0  | 3179 | 1.5184          | 0.7423 |
| 0.0103        | 12.0  | 3468 | 1.6009          | 0.7420 |
| 0.0123        | 13.0  | 3757 | 1.6395          | 0.7402 |
| 0.008         | 14.0  | 4046 | 1.6838          | 0.7429 |
| 0.008         | 15.0  | 4335 | 1.6176          | 0.7490 |
| 0.0012        | 16.0  | 4624 | 1.7873          | 0.7345 |
| 0.0012        | 17.0  | 4913 | 1.6761          | 0.7412 |
| 0.0044        | 18.0  | 5202 | 1.7356          | 0.7417 |
| 0.0044        | 19.0  | 5491 | 1.7686          | 0.7502 |
| 0.0045        | 20.0  | 5780 | 1.7668          | 0.7406 |
| 0.0017        | 21.0  | 6069 | 1.8411          | 0.7381 |
| 0.0017        | 22.0  | 6358 | 1.8147          | 0.7469 |
| 0.0012        | 23.0  | 6647 | 1.8028          | 0.7489 |
| 0.0012        | 24.0  | 6936 | 1.8147          | 0.7453 |
| 0.0026        | 25.0  | 7225 | 1.8257          | 0.7475 |


### 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_4_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\_4\_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: 1.2981
* F1: 0.7565


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