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# xlnet-base-cased_fold_5_binary_v1

This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7395
- F1: 0.8206

## 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   | 288  | 0.4246          | 0.8154 |
| 0.4211        | 2.0   | 576  | 0.5181          | 0.8063 |
| 0.4211        | 3.0   | 864  | 0.4939          | 0.8149 |
| 0.2483        | 4.0   | 1152 | 0.6181          | 0.8227 |
| 0.2483        | 5.0   | 1440 | 0.9251          | 0.8006 |
| 0.1512        | 6.0   | 1728 | 0.9639          | 0.8082 |
| 0.0858        | 7.0   | 2016 | 1.1315          | 0.8074 |
| 0.0858        | 8.0   | 2304 | 1.1322          | 0.8303 |
| 0.053         | 9.0   | 2592 | 1.3171          | 0.8017 |
| 0.053         | 10.0  | 2880 | 1.3729          | 0.8100 |
| 0.0325        | 11.0  | 3168 | 1.2708          | 0.8252 |
| 0.0325        | 12.0  | 3456 | 1.5105          | 0.8242 |
| 0.0203        | 13.0  | 3744 | 1.4902          | 0.8233 |
| 0.0179        | 14.0  | 4032 | 1.5874          | 0.8194 |
| 0.0179        | 15.0  | 4320 | 1.5933          | 0.8135 |
| 0.0174        | 16.0  | 4608 | 1.5908          | 0.8088 |
| 0.0174        | 17.0  | 4896 | 1.5692          | 0.8249 |
| 0.0129        | 18.0  | 5184 | 1.6597          | 0.8167 |
| 0.0129        | 19.0  | 5472 | 1.6009          | 0.8218 |
| 0.0095        | 20.0  | 5760 | 1.6962          | 0.8225 |
| 0.0062        | 21.0  | 6048 | 1.7075          | 0.8182 |
| 0.0062        | 22.0  | 6336 | 1.7335          | 0.8181 |
| 0.0077        | 23.0  | 6624 | 1.7175          | 0.8204 |
| 0.0077        | 24.0  | 6912 | 1.7680          | 0.8187 |
| 0.0024        | 25.0  | 7200 | 1.7395          | 0.8206 |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "xlnet-base-cased_fold_5_binary_v1", "results": []}]}
transformers pytorch tensorboard xlnet text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #xlnet #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

xlnet-base-cased\_fold\_5\_binary\_v1
=====================================


This model is a fine-tuned version of xlnet-base-cased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.7395
* F1: 0.8206


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 4.21.1
* 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 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #xlnet #text-classification #generated_from_trainer #license-mit #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 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #xlnet #text-classification #generated_from_trainer #license-mit #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 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1