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# distilbert-base-uncased_fold_3_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: 1.7987
- F1: 0.7460

## 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  | 0.5903          | 0.6893 |
| 0.5417        | 2.0   | 578  | 0.5822          | 0.7130 |
| 0.5417        | 3.0   | 867  | 0.6471          | 0.7385 |
| 0.2298        | 4.0   | 1156 | 0.8933          | 0.7322 |
| 0.2298        | 5.0   | 1445 | 1.1002          | 0.7147 |
| 0.1012        | 6.0   | 1734 | 1.2041          | 0.7249 |
| 0.0508        | 7.0   | 2023 | 1.3575          | 0.7195 |
| 0.0508        | 8.0   | 2312 | 1.3896          | 0.7385 |
| 0.018         | 9.0   | 2601 | 1.5363          | 0.7238 |
| 0.018         | 10.0  | 2890 | 1.5336          | 0.7364 |
| 0.0142        | 11.0  | 3179 | 1.6335          | 0.7308 |
| 0.0142        | 12.0  | 3468 | 1.6915          | 0.7295 |
| 0.0047        | 13.0  | 3757 | 1.7087          | 0.7427 |
| 0.0058        | 14.0  | 4046 | 1.7875          | 0.7378 |
| 0.0058        | 15.0  | 4335 | 1.7649          | 0.7438 |
| 0.0051        | 16.0  | 4624 | 1.7987          | 0.7460 |
| 0.0051        | 17.0  | 4913 | 1.8435          | 0.7404 |
| 0.0025        | 18.0  | 5202 | 1.9623          | 0.7257 |
| 0.0025        | 19.0  | 5491 | 1.9005          | 0.7304 |
| 0.0029        | 20.0  | 5780 | 1.9437          | 0.7374 |
| 0.0011        | 21.0  | 6069 | 1.9840          | 0.7268 |
| 0.0011        | 22.0  | 6358 | 1.9411          | 0.7346 |
| 0.0025        | 23.0  | 6647 | 1.9233          | 0.7438 |
| 0.0025        | 24.0  | 6936 | 1.9415          | 0.7395 |
| 0.0015        | 25.0  | 7225 | 1.9481          | 0.7411 |


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


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: 1.7987
* F1: 0.7460


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