
<!-- 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. -->

# xtremedistil-l12-h384-uncased-finetuned-wikitext103

This model is a fine-tuned version of [microsoft/xtremedistil-l12-h384-uncased](https://huggingface.co/microsoft/xtremedistil-l12-h384-uncased) on the wikitext dataset.
It achieves the following results on the evaluation set:
- Loss: 6.7699

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 7.3467        | 1.0   | 3125 | 6.9197          |
| 6.9751        | 2.0   | 6250 | 6.8061          |
| 6.9142        | 3.0   | 9375 | 6.7699          |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.11.0
- Datasets 1.1.1
- Tokenizers 0.10.1

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["wikitext"], "model-index": [{"name": "xtremedistil-l12-h384-uncased-finetuned-wikitext103", "results": []}]}
transformers pytorch tensorboard bert fill-mask generated_from_trainer dataset:wikitext license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #dataset-wikitext #license-mit #autotrain_compatible #endpoints_compatible #region-us 

xtremedistil-l12-h384-uncased-finetuned-wikitext103
===================================================


This model is a fine-tuned version of microsoft/xtremedistil-l12-h384-uncased on the wikitext dataset.
It achieves the following results on the evaluation set:


* Loss: 6.7699


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: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3.0


### Training results



### Framework versions


* Transformers 4.16.2
* Pytorch 1.11.0
* Datasets 1.1.1
* Tokenizers 0.10.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3.0 ### Training results ### Framework versions


* Transformers 4.16.2
* Pytorch 1.11.0
* Datasets 1.1.1
* Tokenizers 0.10.1
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #dataset-wikitext #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3.0 ### Training results ### Framework versions


* Transformers 4.16.2
* Pytorch 1.11.0
* Datasets 1.1.1
* Tokenizers 0.10.1
passage: TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #dataset-wikitext #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3.0### Training results### Framework versions


* Transformers 4.16.2
* Pytorch 1.11.0
* Datasets 1.1.1
* Tokenizers 0.10.1