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# xlnet-base-cased-IUChatbot-ontologyDts-localParams

This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0238

## 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: 8
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1172        | 1.0   | 1119 | 0.0657          |
| 0.0564        | 2.0   | 2238 | 0.0237          |
| 0.033         | 3.0   | 3357 | 0.0238          |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.0
- Tokenizers 0.10.3

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "xlnet-base-cased-IUChatbot-ontologyDts-localParams", "results": []}]}
transformers pytorch tensorboard xlnet question-answering generated_from_trainer license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #xlnet #question-answering #generated_from_trainer #license-mit #endpoints_compatible #region-us 

xlnet-base-cased-IUChatbot-ontologyDts-localParams
==================================================


This model is a fine-tuned version of xlnet-base-cased on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0238


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: 8
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3


### Training results



### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.0+cu111
* Datasets 1.18.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.0+cu111
* Datasets 1.18.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #xlnet #question-answering #generated_from_trainer #license-mit #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.0+cu111
* Datasets 1.18.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #xlnet #question-answering #generated_from_trainer #license-mit #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3### Training results### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.0+cu111
* Datasets 1.18.0
* Tokenizers 0.10.3