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# distilbert-base-uncased-finetuned-squad

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0629

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 4    | 5.6141          |
| No log        | 2.0   | 8    | 4.6457          |
| No log        | 3.0   | 12   | 3.9387          |
| No log        | 4.0   | 16   | 3.1467          |
| No log        | 5.0   | 20   | 2.3827          |
| No log        | 6.0   | 24   | 1.9844          |
| No log        | 7.0   | 28   | 1.7256          |
| No log        | 8.0   | 32   | 1.5568          |
| No log        | 9.0   | 36   | 1.3831          |
| No log        | 10.0  | 40   | 1.2769          |
| No log        | 11.0  | 44   | 1.2855          |
| No log        | 12.0  | 48   | 1.1126          |
| No log        | 13.0  | 52   | 1.1142          |
| No log        | 14.0  | 56   | 1.2023          |
| No log        | 15.0  | 60   | 1.1673          |
| No log        | 16.0  | 64   | 1.1534          |
| No log        | 17.0  | 68   | 1.2009          |
| No log        | 18.0  | 72   | 1.1737          |
| No log        | 19.0  | 76   | 1.1303          |
| No log        | 20.0  | 80   | 1.0276          |
| No log        | 21.0  | 84   | 1.0561          |
| No log        | 22.0  | 88   | 1.0313          |
| No log        | 23.0  | 92   | 1.0517          |
| No log        | 24.0  | 96   | 1.0312          |
| No log        | 25.0  | 100  | 1.0145          |
| No log        | 26.0  | 104  | 1.0391          |
| No log        | 27.0  | 108  | 1.0543          |
| No log        | 28.0  | 112  | 1.0626          |
| No log        | 29.0  | 116  | 1.0653          |
| No log        | 30.0  | 120  | 1.0629          |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.10.0+cu113
- Datasets 2.10.1
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "distilbert-base-uncased-finetuned-squad", "results": []}]}
transformers pytorch tensorboard distilbert question-answering generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #distilbert #question-answering #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

distilbert-base-uncased-finetuned-squad
=======================================


This model is a fine-tuned version of distilbert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.0629


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: 30


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.10.0+cu113
* Datasets 2.10.1
* Tokenizers 0.12.1



### 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: 30 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.10.0+cu113
* Datasets 2.10.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #distilbert #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: 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: 30 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.10.0+cu113
* Datasets 2.10.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #distilbert #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: 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: 30### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.10.0+cu113
* Datasets 2.10.1
* Tokenizers 0.12.1