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# xlnet-base-cased_fold_2_binary

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: 0.4858
- F1: 0.7648

## 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   | 290  | 0.4361          | 0.7404 |
| 0.4403        | 2.0   | 580  | 0.5363          | 0.7515 |
| 0.4403        | 3.0   | 870  | 0.4858          | 0.7648 |
| 0.2505        | 4.0   | 1160 | 0.7127          | 0.7612 |
| 0.2505        | 5.0   | 1450 | 0.8930          | 0.7554 |
| 0.1425        | 6.0   | 1740 | 0.9897          | 0.7580 |
| 0.0869        | 7.0   | 2030 | 1.2683          | 0.7615 |
| 0.0869        | 8.0   | 2320 | 1.4988          | 0.7343 |
| 0.0411        | 9.0   | 2610 | 1.5082          | 0.7492 |
| 0.0411        | 10.0  | 2900 | 1.4974          | 0.7450 |
| 0.0306        | 11.0  | 3190 | 1.5723          | 0.7435 |
| 0.0306        | 12.0  | 3480 | 1.8446          | 0.7432 |
| 0.0291        | 13.0  | 3770 | 1.7113          | 0.7639 |
| 0.0207        | 14.0  | 4060 | 1.8073          | 0.7394 |
| 0.0207        | 15.0  | 4350 | 1.7524          | 0.7585 |
| 0.0171        | 16.0  | 4640 | 1.8751          | 0.7374 |
| 0.0171        | 17.0  | 4930 | 1.7849          | 0.7561 |
| 0.0084        | 18.0  | 5220 | 1.8618          | 0.7441 |
| 0.0064        | 19.0  | 5510 | 1.9613          | 0.7437 |
| 0.0064        | 20.0  | 5800 | 1.8898          | 0.7430 |
| 0.006         | 21.0  | 6090 | 1.9889          | 0.7409 |
| 0.006         | 22.0  | 6380 | 1.9949          | 0.7488 |
| 0.0049        | 23.0  | 6670 | 1.9453          | 0.7488 |
| 0.0049        | 24.0  | 6960 | 1.9754          | 0.7472 |
| 0.002         | 25.0  | 7250 | 1.9946          | 0.7504 |


### Framework versions

- Transformers 4.21.0
- 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_2_binary", "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\_2\_binary
=================================


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: 0.4858
* F1: 0.7648


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 #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 4.21.0
* 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 4.21.0
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1