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# distilbert-base-uncased_fold_2_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: 1.5810
- F1: 0.7620

## 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  | 0.5886          | 0.7239 |
| 0.557         | 2.0   | 588  | 0.5085          | 0.7524 |
| 0.557         | 3.0   | 882  | 0.6332          | 0.7530 |
| 0.2456        | 4.0   | 1176 | 0.8749          | 0.7161 |
| 0.2456        | 5.0   | 1470 | 1.0601          | 0.7371 |
| 0.1112        | 6.0   | 1764 | 1.1885          | 0.7451 |
| 0.0484        | 7.0   | 2058 | 1.3027          | 0.7240 |
| 0.0484        | 8.0   | 2352 | 1.4647          | 0.7259 |
| 0.0259        | 9.0   | 2646 | 1.4476          | 0.7322 |
| 0.0259        | 10.0  | 2940 | 1.4826          | 0.7388 |
| 0.0164        | 11.0  | 3234 | 1.5869          | 0.7333 |
| 0.0109        | 12.0  | 3528 | 1.5954          | 0.7539 |
| 0.0109        | 13.0  | 3822 | 1.5810          | 0.7620 |
| 0.0082        | 14.0  | 4116 | 1.7165          | 0.7335 |
| 0.0082        | 15.0  | 4410 | 1.8152          | 0.7414 |
| 0.004         | 16.0  | 4704 | 1.7411          | 0.7474 |
| 0.004         | 17.0  | 4998 | 1.8692          | 0.7355 |
| 0.0034        | 18.0  | 5292 | 1.8727          | 0.7303 |
| 0.0009        | 19.0  | 5586 | 1.9813          | 0.7305 |
| 0.0009        | 20.0  | 5880 | 1.9764          | 0.7391 |
| 0.0012        | 21.0  | 6174 | 2.0170          | 0.7291 |
| 0.0012        | 22.0  | 6468 | 2.0240          | 0.7391 |
| 0.0004        | 23.0  | 6762 | 2.0311          | 0.7352 |
| 0.0014        | 24.0  | 7056 | 2.0174          | 0.7334 |
| 0.0014        | 25.0  | 7350 | 2.0282          | 0.7381 |


### 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", "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
=========================================


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: 1.5810
* F1: 0.7620


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