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# bert_large_subjqa_model_v3

This model is a fine-tuned version of [bert-large-uncased-whole-word-masking-finetuned-squad](https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 8.8423

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 410  | 2.3971          |
| 2.5672        | 2.0   | 820  | 2.7380          |
| 1.6385        | 3.0   | 1230 | 3.1387          |
| 0.8467        | 4.0   | 1640 | 4.0478          |
| 0.4177        | 5.0   | 2050 | 4.9824          |
| 0.4177        | 6.0   | 2460 | 5.5992          |
| 0.2208        | 7.0   | 2870 | 6.2417          |
| 0.1469        | 8.0   | 3280 | 7.1139          |
| 0.0966        | 9.0   | 3690 | 8.0166          |
| 0.0746        | 10.0  | 4100 | 7.7937          |
| 0.0589        | 11.0  | 4510 | 7.8738          |
| 0.0589        | 12.0  | 4920 | 8.3362          |
| 0.0439        | 13.0  | 5330 | 8.6546          |
| 0.0388        | 14.0  | 5740 | 8.8050          |
| 0.029         | 15.0  | 6150 | 8.8423          |


### Framework versions

- Transformers 4.28.0
- Pytorch 1.13.0a0+d321be6
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "bert_large_subjqa_model_v3", "results": []}]}
transformers pytorch tensorboard bert question-answering generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

bert\_large\_subjqa\_model\_v3
==============================


This model is a fine-tuned version of bert-large-uncased-whole-word-masking-finetuned-squad on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 8.8423


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: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 1.13.0a0+d321be6
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 1.13.0a0+d321be6
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 1.13.0a0+d321be6
* Datasets 2.12.0
* Tokenizers 0.13.3