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# bert-small-finetuned-finetuned-parsed-longer50

This model is a fine-tuned version of [muhtasham/bert-small-finetuned-parsed20](https://huggingface.co/muhtasham/bert-small-finetuned-parsed20) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9278

## 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: 128
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 4    | 2.9807          |
| No log        | 2.0   | 8    | 2.7267          |
| No log        | 3.0   | 12   | 3.3484          |
| No log        | 4.0   | 16   | 2.7573          |
| No log        | 5.0   | 20   | 2.7063          |
| No log        | 6.0   | 24   | 2.7353          |
| No log        | 7.0   | 28   | 3.1290          |
| No log        | 8.0   | 32   | 2.9371          |
| No log        | 9.0   | 36   | 3.4265          |
| No log        | 10.0  | 40   | 3.0537          |
| No log        | 11.0  | 44   | 3.1382          |
| No log        | 12.0  | 48   | 3.1454          |
| No log        | 13.0  | 52   | 2.8379          |
| No log        | 14.0  | 56   | 3.2760          |
| No log        | 15.0  | 60   | 3.0504          |
| No log        | 16.0  | 64   | 2.9001          |
| No log        | 17.0  | 68   | 2.8892          |
| No log        | 18.0  | 72   | 3.1837          |
| No log        | 19.0  | 76   | 2.6404          |
| No log        | 20.0  | 80   | 3.0600          |
| No log        | 21.0  | 84   | 3.1432          |
| No log        | 22.0  | 88   | 2.9608          |
| No log        | 23.0  | 92   | 3.0513          |
| No log        | 24.0  | 96   | 3.1038          |
| No log        | 25.0  | 100  | 3.0975          |
| No log        | 26.0  | 104  | 2.8977          |
| No log        | 27.0  | 108  | 2.9416          |
| No log        | 28.0  | 112  | 2.9015          |
| No log        | 29.0  | 116  | 2.7947          |
| No log        | 30.0  | 120  | 2.9278          |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "bert-small-finetuned-finetuned-parsed-longer50", "results": []}]}
transformers pytorch tensorboard bert fill-mask generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

bert-small-finetuned-finetuned-parsed-longer50
==============================================


This model is a fine-tuned version of muhtasham/bert-small-finetuned-parsed20 on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 2.9278


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: 128
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30


### Training results



### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+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: 128
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 128
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 128
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30### Training results### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1