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# bert-base-uncased-pretrain-finetuned-coqa-falt

This model is a fine-tuned version of [alistvt/bert-base-uncased-pretrained-mlm-coqa-stories](https://huggingface.co/alistvt/bert-base-uncased-pretrained-mlm-coqa-stories) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8125

## 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: 1e-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: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 3.4039        | 0.29  | 2000  | 3.0921          |
| 3.1438        | 0.59  | 4000  | 2.8826          |
| 3.0252        | 0.88  | 6000  | 2.7885          |
| 2.7112        | 1.18  | 8000  | 2.7720          |
| 2.6703        | 1.47  | 10000 | 2.7581          |
| 2.6432        | 1.77  | 12000 | 2.7316          |
| 2.385         | 2.06  | 14000 | 2.7798          |
| 2.3314        | 2.36  | 16000 | 2.7836          |
| 2.3433        | 2.65  | 18000 | 2.7650          |
| 2.3604        | 2.95  | 20000 | 2.7585          |
| 2.2232        | 3.24  | 22000 | 2.8120          |
| 2.2094        | 3.53  | 24000 | 2.7945          |
| 2.2306        | 3.83  | 26000 | 2.8125          |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.0
- Tokenizers 0.10.3

{"tags": ["generated_from_trainer"], "model-index": [{"name": "bert-base-uncased-pretrain-finetuned-coqa-falt", "results": []}]}
transformers pytorch tensorboard bert question-answering generated_from_trainer endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #endpoints_compatible #region-us 

bert-base-uncased-pretrain-finetuned-coqa-falt
==============================================


This model is a fine-tuned version of alistvt/bert-base-uncased-pretrained-mlm-coqa-stories on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.8125


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: 1e-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: 4


### Training results



### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.0+cu111
* Datasets 1.18.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-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: 4 ### Training results ### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.0+cu111
* Datasets 1.18.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-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: 4 ### Training results ### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.0+cu111
* Datasets 1.18.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-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: 4### Training results### Framework versions


* Transformers 4.15.0
* Pytorch 1.10.0+cu111
* Datasets 1.18.0
* Tokenizers 0.10.3