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# xlnet-base-cased_fold_7_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: 1.7774
- F1: 0.8111

## 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  | 0.4189          | 0.7903 |
| 0.432         | 2.0   | 576  | 0.3927          | 0.8045 |
| 0.432         | 3.0   | 864  | 0.4868          | 0.8108 |
| 0.2573        | 4.0   | 1152 | 0.6763          | 0.8019 |
| 0.2573        | 5.0   | 1440 | 0.8132          | 0.8105 |
| 0.1612        | 6.0   | 1728 | 0.8544          | 0.8086 |
| 0.0972        | 7.0   | 2016 | 1.1274          | 0.8109 |
| 0.0972        | 8.0   | 2304 | 1.2622          | 0.8056 |
| 0.0515        | 9.0   | 2592 | 1.3398          | 0.8013 |
| 0.0515        | 10.0  | 2880 | 1.5421          | 0.8082 |
| 0.0244        | 11.0  | 3168 | 1.4931          | 0.8042 |
| 0.0244        | 12.0  | 3456 | 1.5744          | 0.8045 |
| 0.0287        | 13.0  | 3744 | 1.4169          | 0.8091 |
| 0.0255        | 14.0  | 4032 | 1.5790          | 0.7999 |
| 0.0255        | 15.0  | 4320 | 1.6094          | 0.7994 |
| 0.0098        | 16.0  | 4608 | 1.5758          | 0.8006 |
| 0.0098        | 17.0  | 4896 | 1.5326          | 0.8140 |
| 0.0203        | 18.0  | 5184 | 1.6431          | 0.8114 |
| 0.0203        | 19.0  | 5472 | 1.7105          | 0.8072 |
| 0.0104        | 20.0  | 5760 | 1.6353          | 0.8139 |
| 0.0062        | 21.0  | 6048 | 1.6762          | 0.8108 |
| 0.0062        | 22.0  | 6336 | 1.7076          | 0.8106 |
| 0.0088        | 23.0  | 6624 | 1.7887          | 0.8035 |
| 0.0088        | 24.0  | 6912 | 1.7731          | 0.8099 |
| 0.0026        | 25.0  | 7200 | 1.7774          | 0.8111 |


### 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_7_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\_7\_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: 1.7774
* F1: 0.8111


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