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# distilbert-base-uncased_fold_6_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: 1.6625
- F1: 0.7588

## 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   | 292  | 0.5117          | 0.7306 |
| 0.5701        | 2.0   | 584  | 0.5273          | 0.7296 |
| 0.5701        | 3.0   | 876  | 0.6037          | 0.7415 |
| 0.2468        | 4.0   | 1168 | 0.7132          | 0.7318 |
| 0.2468        | 5.0   | 1460 | 0.8980          | 0.7504 |
| 0.12          | 6.0   | 1752 | 1.0343          | 0.7369 |
| 0.0486        | 7.0   | 2044 | 1.1860          | 0.7333 |
| 0.0486        | 8.0   | 2336 | 1.3348          | 0.7437 |
| 0.019         | 9.0   | 2628 | 1.3040          | 0.7561 |
| 0.019         | 10.0  | 2920 | 1.4649          | 0.7293 |
| 0.0152        | 11.0  | 3212 | 1.4870          | 0.7431 |
| 0.0078        | 12.0  | 3504 | 1.5668          | 0.7455 |
| 0.0078        | 13.0  | 3796 | 1.5280          | 0.7378 |
| 0.0091        | 14.0  | 4088 | 1.5672          | 0.7410 |
| 0.0091        | 15.0  | 4380 | 1.5948          | 0.7491 |
| 0.0052        | 16.0  | 4672 | 1.6625          | 0.7588 |
| 0.0052        | 17.0  | 4964 | 1.6544          | 0.7411 |
| 0.0048        | 18.0  | 5256 | 1.7124          | 0.7425 |
| 0.0024        | 19.0  | 5548 | 1.7211          | 0.7477 |
| 0.0024        | 20.0  | 5840 | 1.8216          | 0.7373 |
| 0.001         | 21.0  | 6132 | 1.8325          | 0.7361 |
| 0.001         | 22.0  | 6424 | 1.8089          | 0.7498 |
| 0.0015        | 23.0  | 6716 | 1.8026          | 0.7506 |
| 0.0005        | 24.0  | 7008 | 1.8026          | 0.7464 |
| 0.0005        | 25.0  | 7300 | 1.8043          | 0.7464 |


### 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_6_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\_6\_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: 1.6625
* F1: 0.7588


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