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# bert-large-uncased-finetuned-vi-infovqa

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 7.4878

## 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: 2
- eval_batch_size: 2
- seed: 250500
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 0.11  | 100  | 4.6256          |
| No log        | 0.21  | 200  | 4.4042          |
| No log        | 0.32  | 300  | 5.0021          |
| No log        | 0.43  | 400  | 4.2825          |
| 4.6758        | 0.53  | 500  | 4.3886          |
| 4.6758        | 0.64  | 600  | 4.2519          |
| 4.6758        | 0.75  | 700  | 4.2977          |
| 4.6758        | 0.85  | 800  | 3.9916          |
| 4.6758        | 0.96  | 900  | 4.1650          |
| 4.1715        | 1.07  | 1000 | 4.5001          |
| 4.1715        | 1.17  | 1100 | 4.0898          |
| 4.1715        | 1.28  | 1200 | 4.1623          |
| 4.1715        | 1.39  | 1300 | 4.3271          |
| 4.1715        | 1.49  | 1400 | 3.9661          |
| 3.7926        | 1.6   | 1500 | 3.8727          |
| 3.7926        | 1.71  | 1600 | 3.8934          |
| 3.7926        | 1.81  | 1700 | 3.7262          |
| 3.7926        | 1.92  | 1800 | 3.7701          |
| 3.7926        | 2.03  | 1900 | 3.7653          |
| 3.5041        | 2.13  | 2000 | 3.9261          |
| 3.5041        | 2.24  | 2100 | 4.0915          |
| 3.5041        | 2.35  | 2200 | 4.0348          |
| 3.5041        | 2.45  | 2300 | 4.0212          |
| 3.5041        | 2.56  | 2400 | 4.4653          |
| 2.8475        | 2.67  | 2500 | 4.2959          |
| 2.8475        | 2.77  | 2600 | 4.1039          |
| 2.8475        | 2.88  | 2700 | 3.8037          |
| 2.8475        | 2.99  | 2800 | 3.7552          |
| 2.8475        | 3.09  | 2900 | 4.2476          |
| 2.5488        | 3.2   | 3000 | 4.6716          |
| 2.5488        | 3.3   | 3100 | 4.7058          |
| 2.5488        | 3.41  | 3200 | 4.6266          |
| 2.5488        | 3.52  | 3300 | 4.5697          |
| 2.5488        | 3.62  | 3400 | 5.1017          |
| 2.0347        | 3.73  | 3500 | 4.6254          |
| 2.0347        | 3.84  | 3600 | 4.4822          |
| 2.0347        | 3.94  | 3700 | 4.9413          |
| 2.0347        | 4.05  | 3800 | 5.3600          |
| 2.0347        | 4.16  | 3900 | 5.7323          |
| 1.6566        | 4.26  | 4000 | 5.8822          |
| 1.6566        | 4.37  | 4100 | 6.0173          |
| 1.6566        | 4.48  | 4200 | 5.6688          |
| 1.6566        | 4.58  | 4300 | 6.0617          |
| 1.6566        | 4.69  | 4400 | 6.6631          |
| 1.3348        | 4.8   | 4500 | 6.0290          |
| 1.3348        | 4.9   | 4600 | 6.2455          |
| 1.3348        | 5.01  | 4700 | 6.0963          |
| 1.3348        | 5.12  | 4800 | 7.0983          |
| 1.3348        | 5.22  | 4900 | 7.5483          |
| 1.0701        | 5.33  | 5000 | 7.7187          |
| 1.0701        | 5.44  | 5100 | 7.4630          |
| 1.0701        | 5.54  | 5200 | 7.1394          |
| 1.0701        | 5.65  | 5300 | 7.0703          |
| 1.0701        | 5.76  | 5400 | 7.5611          |
| 0.9414        | 5.86  | 5500 | 7.6038          |
| 0.9414        | 5.97  | 5600 | 7.4878          |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "bert-large-uncased-finetuned-vi-infovqa", "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-uncased-finetuned-vi-infovqa
=======================================


This model is a fine-tuned version of bert-large-uncased on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 7.4878


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: 2
* eval\_batch\_size: 2
* seed: 250500
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6


### Training results



### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.0+cu111
* Datasets 1.17.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 250500
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6 ### Training results ### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.0+cu111
* Datasets 1.17.0
* Tokenizers 0.10.3
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: 2
* eval\_batch\_size: 2
* seed: 250500
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6 ### Training results ### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.0+cu111
* Datasets 1.17.0
* Tokenizers 0.10.3
passage: 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: 2
* eval\_batch\_size: 2
* seed: 250500
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6### Training results### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.0+cu111
* Datasets 1.17.0
* Tokenizers 0.10.3