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# bert-large-uncased-whole-word-masking-squad

This model is a fine-tuned version of [deepset/bert-large-uncased-whole-word-masking-squad2](https://huggingface.co/deepset/bert-large-uncased-whole-word-masking-squad2) on the squad dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3100

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 250  | 0.1796          |
| 0.21          | 2.0   | 500  | 0.2187          |
| 0.21          | 3.0   | 750  | 0.3100          |


### Framework versions

- Transformers 4.27.3
- Pytorch 2.0.0
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "cc-by-4.0", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "bert-large-uncased-whole-word-masking-squad", "results": []}]}
transformers pytorch bert question-answering generated_from_trainer dataset:squad license:cc-by-4.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #question-answering #generated_from_trainer #dataset-squad #license-cc-by-4.0 #endpoints_compatible #region-us 

bert-large-uncased-whole-word-masking-squad
===========================================


This model is a fine-tuned version of deepset/bert-large-uncased-whole-word-masking-squad2 on the squad dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3100


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: 3


### Training results



### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0
* Datasets 2.10.1
* Tokenizers 0.13.2



### 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: 3 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #question-answering #generated_from_trainer #dataset-squad #license-cc-by-4.0 #endpoints_compatible #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: 3 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #question-answering #generated_from_trainer #dataset-squad #license-cc-by-4.0 #endpoints_compatible #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: 3### Training results### Framework versions


* Transformers 4.27.3
* Pytorch 2.0.0
* Datasets 2.10.1
* Tokenizers 0.13.2