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# xlnet-base-cased_fold_8_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: 1.5333
- F1: 0.8407

## 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  | 0.3866          | 0.8172 |
| 0.4299        | 2.0   | 580  | 0.4215          | 0.8246 |
| 0.4299        | 3.0   | 870  | 0.4765          | 0.8238 |
| 0.2564        | 4.0   | 1160 | 0.7283          | 0.8350 |
| 0.2564        | 5.0   | 1450 | 0.6825          | 0.8363 |
| 0.1553        | 6.0   | 1740 | 0.9637          | 0.8339 |
| 0.0893        | 7.0   | 2030 | 1.1392          | 0.8239 |
| 0.0893        | 8.0   | 2320 | 1.1868          | 0.8231 |
| 0.0538        | 9.0   | 2610 | 1.2180          | 0.8346 |
| 0.0538        | 10.0  | 2900 | 1.2353          | 0.8253 |
| 0.0386        | 11.0  | 3190 | 1.1883          | 0.8317 |
| 0.0386        | 12.0  | 3480 | 1.2786          | 0.8375 |
| 0.0289        | 13.0  | 3770 | 1.3725          | 0.8375 |
| 0.0146        | 14.0  | 4060 | 1.3171          | 0.8463 |
| 0.0146        | 15.0  | 4350 | 1.2323          | 0.8425 |
| 0.0182        | 16.0  | 4640 | 1.3169          | 0.8485 |
| 0.0182        | 17.0  | 4930 | 1.4424          | 0.8336 |
| 0.0125        | 18.0  | 5220 | 1.4336          | 0.8385 |
| 0.0102        | 19.0  | 5510 | 1.4888          | 0.8405 |
| 0.0102        | 20.0  | 5800 | 1.5227          | 0.8419 |
| 0.0035        | 21.0  | 6090 | 1.4994          | 0.8421 |
| 0.0035        | 22.0  | 6380 | 1.4845          | 0.8424 |
| 0.0047        | 23.0  | 6670 | 1.5006          | 0.8422 |
| 0.0047        | 24.0  | 6960 | 1.5468          | 0.8422 |
| 0.0042        | 25.0  | 7250 | 1.5333          | 0.8407 |


### 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_8_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\_8\_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: 1.5333
* F1: 0.8407


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