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# xlnet-base-cased_fold_9_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: 1.7204
- F1: 0.8203

## 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   | 291  | 0.4045          | 0.8001 |
| 0.4262        | 2.0   | 582  | 0.3914          | 0.8297 |
| 0.4262        | 3.0   | 873  | 0.5050          | 0.8029 |
| 0.2488        | 4.0   | 1164 | 0.7681          | 0.8007 |
| 0.2488        | 5.0   | 1455 | 0.8349          | 0.8262 |
| 0.1483        | 6.0   | 1746 | 0.9045          | 0.8220 |
| 0.0894        | 7.0   | 2037 | 1.1584          | 0.8165 |
| 0.0894        | 8.0   | 2328 | 1.1818          | 0.8300 |
| 0.0389        | 9.0   | 2619 | 1.3332          | 0.8147 |
| 0.0389        | 10.0  | 2910 | 1.2373          | 0.8285 |
| 0.038         | 11.0  | 3201 | 1.3156          | 0.8234 |
| 0.038         | 12.0  | 3492 | 1.3251          | 0.8341 |
| 0.0211        | 13.0  | 3783 | 1.3144          | 0.8255 |
| 0.0158        | 14.0  | 4074 | 1.5686          | 0.8168 |
| 0.0158        | 15.0  | 4365 | 1.5382          | 0.8185 |
| 0.0165        | 16.0  | 4656 | 1.5203          | 0.8282 |
| 0.0165        | 17.0  | 4947 | 1.5352          | 0.8136 |
| 0.0142        | 18.0  | 5238 | 1.4799          | 0.8243 |
| 0.0062        | 19.0  | 5529 | 1.5030          | 0.8294 |
| 0.0062        | 20.0  | 5820 | 1.6264          | 0.8094 |
| 0.0078        | 21.0  | 6111 | 1.6949          | 0.8122 |
| 0.0078        | 22.0  | 6402 | 1.7106          | 0.8139 |
| 0.0043        | 23.0  | 6693 | 1.7234          | 0.8218 |
| 0.0043        | 24.0  | 6984 | 1.7344          | 0.8208 |
| 0.0028        | 25.0  | 7275 | 1.7204          | 0.8203 |


### 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_9_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\_9\_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: 1.7204
* F1: 0.8203


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