
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# gpt2-token-class

This model is a fine-tuned version of [brad1141/gpt2-finetuned-comp2](https://huggingface.co/brad1141/gpt2-finetuned-comp2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3182

## 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: 7

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.3177        | 1.0   | 1796  | 0.3182          |
| 0.2947        | 2.0   | 3592  | 0.3122          |
| 0.2808        | 3.0   | 5388  | 0.3087          |
| 0.2657        | 4.0   | 7184  | 0.3124          |
| 0.2537        | 5.0   | 8980  | 0.3134          |
| 0.2446        | 6.0   | 10776 | 0.3143          |
| 0.2387        | 7.0   | 12572 | 0.3182          |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "gpt2-token-class", "results": []}]}
transformers pytorch tensorboard gpt2 token-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #gpt2 #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

gpt2-token-class
================


This model is a fine-tuned version of brad1141/gpt2-finetuned-comp2 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3182


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: 7


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### 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: 7 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #gpt2 #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #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: 7 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3