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# distilroberta-base-finetuned-squad2-lwt

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the squad_v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1356

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.1702        | 1.0   | 4120  | 1.1220          |
| 0.9787        | 2.0   | 8240  | 1.0500          |
| 0.8153        | 3.0   | 12360 | 1.1356          |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6

{'HasAns_exact': 71.39001349527665,
 'HasAns_f1': 77.71740687727831,
 'HasAns_total': 5928,
 'NoAns_exact': 68.59545836837678,
 'NoAns_f1': 68.59545836837678,
 'NoAns_total': 5945,
 'best_exact': 69.9991577528847,
 'best_exact_thresh': 0.0,
 'best_f1': 73.1583245993857,
 'best_f1_thresh': 0.0,
 'exact': 69.99073528173166,
 'f1': 73.1499021282327,
 'total': 11873}
{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad_v2"], "model-index": [{"name": "distilroberta-base-finetuned-squad2-lwt", "results": []}]}
transformers pytorch tensorboard roberta question-answering generated_from_trainer dataset:squad_v2 license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #question-answering #generated_from_trainer #dataset-squad_v2 #license-apache-2.0 #endpoints_compatible #region-us 

distilroberta-base-finetuned-squad2-lwt
=======================================


This model is a fine-tuned version of distilroberta-base on the squad\_v2 dataset.
It achieves the following results on the evaluation set:


* Loss: 1.1356


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: 32
* eval\_batch\_size: 32
* 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 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6


{'HasAns\_exact': 71.39001349527665,
'HasAns\_f1': 77.71740687727831,
'HasAns\_total': 5928,
'NoAns\_exact': 68.59545836837678,
'NoAns\_f1': 68.59545836837678,
'NoAns\_total': 5945,
'best\_exact': 69.9991577528847,
'best\_exact\_thresh': 0.0,
'best\_f1': 73.1583245993857,
'best\_f1\_thresh': 0.0,
'exact': 69.99073528173166,
'f1': 73.1499021282327,
'total': 11873}



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6


{'HasAns\_exact': 71.39001349527665,
'HasAns\_f1': 77.71740687727831,
'HasAns\_total': 5928,
'NoAns\_exact': 68.59545836837678,
'NoAns\_f1': 68.59545836837678,
'NoAns\_total': 5945,
'best\_exact': 69.9991577528847,
'best\_exact\_thresh': 0.0,
'best\_f1': 73.1583245993857,
'best\_f1\_thresh': 0.0,
'exact': 69.99073528173166,
'f1': 73.1499021282327,
'total': 11873}
TAGS
#transformers #pytorch #tensorboard #roberta #question-answering #generated_from_trainer #dataset-squad_v2 #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6


{'HasAns\_exact': 71.39001349527665,
'HasAns\_f1': 77.71740687727831,
'HasAns\_total': 5928,
'NoAns\_exact': 68.59545836837678,
'NoAns\_f1': 68.59545836837678,
'NoAns\_total': 5945,
'best\_exact': 69.9991577528847,
'best\_exact\_thresh': 0.0,
'best\_f1': 73.1583245993857,
'best\_f1\_thresh': 0.0,
'exact': 69.99073528173166,
'f1': 73.1499021282327,
'total': 11873}
passage: TAGS
#transformers #pytorch #tensorboard #roberta #question-answering #generated_from_trainer #dataset-squad_v2 #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6


{'HasAns\_exact': 71.39001349527665,
'HasAns\_f1': 77.71740687727831,
'HasAns\_total': 5928,
'NoAns\_exact': 68.59545836837678,
'NoAns\_f1': 68.59545836837678,
'NoAns\_total': 5945,
'best\_exact': 69.9991577528847,
'best\_exact\_thresh': 0.0,
'best\_f1': 73.1583245993857,
'best\_f1\_thresh': 0.0,
'exact': 69.99073528173166,
'f1': 73.1499021282327,
'total': 11873}