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# xlnet-base-cased_fold_3_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: 1.8649
- F1: 0.8044

## 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   | 289  | 0.4483          | 0.8000 |
| 0.4228        | 2.0   | 578  | 0.4264          | 0.8040 |
| 0.4228        | 3.0   | 867  | 0.5341          | 0.8056 |
| 0.2409        | 4.0   | 1156 | 0.9077          | 0.8103 |
| 0.2409        | 5.0   | 1445 | 1.1069          | 0.7889 |
| 0.1386        | 6.0   | 1734 | 1.0288          | 0.8093 |
| 0.0817        | 7.0   | 2023 | 1.2477          | 0.8049 |
| 0.0817        | 8.0   | 2312 | 1.5915          | 0.7872 |
| 0.0465        | 9.0   | 2601 | 1.5323          | 0.8035 |
| 0.0465        | 10.0  | 2890 | 1.4351          | 0.7989 |
| 0.0376        | 11.0  | 3179 | 1.4639          | 0.7916 |
| 0.0376        | 12.0  | 3468 | 1.6027          | 0.7956 |
| 0.0234        | 13.0  | 3757 | 1.7860          | 0.7931 |
| 0.0109        | 14.0  | 4046 | 1.8567          | 0.7934 |
| 0.0109        | 15.0  | 4335 | 1.8294          | 0.8053 |
| 0.0115        | 16.0  | 4624 | 1.7799          | 0.7971 |
| 0.0115        | 17.0  | 4913 | 1.5935          | 0.8000 |
| 0.0142        | 18.0  | 5202 | 1.8136          | 0.8066 |
| 0.0142        | 19.0  | 5491 | 1.7718          | 0.8063 |
| 0.0124        | 20.0  | 5780 | 1.8581          | 0.8053 |
| 0.0083        | 21.0  | 6069 | 1.8523          | 0.8056 |
| 0.0083        | 22.0  | 6358 | 1.8408          | 0.8035 |
| 0.0045        | 23.0  | 6647 | 1.8347          | 0.8040 |
| 0.0045        | 24.0  | 6936 | 1.8683          | 0.8067 |
| 0.0005        | 25.0  | 7225 | 1.8649          | 0.8044 |


### 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_3_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\_3\_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: 1.8649
* F1: 0.8044


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