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# distilbert-base-cased-distilled-squad-finetuned-lr1e-08-epochs100

This model is a fine-tuned version of [distilbert-base-cased-distilled-squad](https://huggingface.co/distilbert-base-cased-distilled-squad) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.7336

## 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-08
- 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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 4    | 4.7927          |
| No log        | 2.0   | 8    | 4.7914          |
| No log        | 3.0   | 12   | 4.7901          |
| No log        | 4.0   | 16   | 4.7888          |
| No log        | 5.0   | 20   | 4.7876          |
| No log        | 6.0   | 24   | 4.7864          |
| No log        | 7.0   | 28   | 4.7851          |
| No log        | 8.0   | 32   | 4.7839          |
| No log        | 9.0   | 36   | 4.7827          |
| No log        | 10.0  | 40   | 4.7815          |
| No log        | 11.0  | 44   | 4.7804          |
| No log        | 12.0  | 48   | 4.7792          |
| No log        | 13.0  | 52   | 4.7781          |
| No log        | 14.0  | 56   | 4.7769          |
| No log        | 15.0  | 60   | 4.7758          |
| No log        | 16.0  | 64   | 4.7747          |
| No log        | 17.0  | 68   | 4.7735          |
| No log        | 18.0  | 72   | 4.7724          |
| No log        | 19.0  | 76   | 4.7713          |
| No log        | 20.0  | 80   | 4.7703          |
| No log        | 21.0  | 84   | 4.7692          |
| No log        | 22.0  | 88   | 4.7682          |
| No log        | 23.0  | 92   | 4.7672          |
| No log        | 24.0  | 96   | 4.7662          |
| No log        | 25.0  | 100  | 4.7652          |
| No log        | 26.0  | 104  | 4.7642          |
| No log        | 27.0  | 108  | 4.7633          |
| No log        | 28.0  | 112  | 4.7623          |
| No log        | 29.0  | 116  | 4.7614          |
| No log        | 30.0  | 120  | 4.7604          |
| No log        | 31.0  | 124  | 4.7595          |
| No log        | 32.0  | 128  | 4.7586          |
| No log        | 33.0  | 132  | 4.7577          |
| No log        | 34.0  | 136  | 4.7569          |
| No log        | 35.0  | 140  | 4.7560          |
| No log        | 36.0  | 144  | 4.7552          |
| No log        | 37.0  | 148  | 4.7544          |
| No log        | 38.0  | 152  | 4.7535          |
| No log        | 39.0  | 156  | 4.7528          |
| No log        | 40.0  | 160  | 4.7520          |
| No log        | 41.0  | 164  | 4.7513          |
| No log        | 42.0  | 168  | 4.7506          |
| No log        | 43.0  | 172  | 4.7499          |
| No log        | 44.0  | 176  | 4.7492          |
| No log        | 45.0  | 180  | 4.7485          |
| No log        | 46.0  | 184  | 4.7478          |
| No log        | 47.0  | 188  | 4.7472          |
| No log        | 48.0  | 192  | 4.7466          |
| No log        | 49.0  | 196  | 4.7460          |
| No log        | 50.0  | 200  | 4.7454          |
| No log        | 51.0  | 204  | 4.7448          |
| No log        | 52.0  | 208  | 4.7442          |
| No log        | 53.0  | 212  | 4.7437          |
| No log        | 54.0  | 216  | 4.7431          |
| No log        | 55.0  | 220  | 4.7426          |
| No log        | 56.0  | 224  | 4.7421          |
| No log        | 57.0  | 228  | 4.7416          |
| No log        | 58.0  | 232  | 4.7411          |
| No log        | 59.0  | 236  | 4.7406          |
| No log        | 60.0  | 240  | 4.7401          |
| No log        | 61.0  | 244  | 4.7397          |
| No log        | 62.0  | 248  | 4.7393          |
| No log        | 63.0  | 252  | 4.7388          |
| No log        | 64.0  | 256  | 4.7385          |
| No log        | 65.0  | 260  | 4.7381          |
| No log        | 66.0  | 264  | 4.7377          |
| No log        | 67.0  | 268  | 4.7374          |
| No log        | 68.0  | 272  | 4.7370          |
| No log        | 69.0  | 276  | 4.7367          |
| No log        | 70.0  | 280  | 4.7364          |
| No log        | 71.0  | 284  | 4.7361          |
| No log        | 72.0  | 288  | 4.7359          |
| No log        | 73.0  | 292  | 4.7356          |
| No log        | 74.0  | 296  | 4.7354          |
| No log        | 75.0  | 300  | 4.7351          |
| No log        | 76.0  | 304  | 4.7349          |
| No log        | 77.0  | 308  | 4.7348          |
| No log        | 78.0  | 312  | 4.7346          |
| No log        | 79.0  | 316  | 4.7345          |
| No log        | 80.0  | 320  | 4.7343          |
| No log        | 81.0  | 324  | 4.7342          |
| No log        | 82.0  | 328  | 4.7341          |
| No log        | 83.0  | 332  | 4.7340          |
| No log        | 84.0  | 336  | 4.7339          |
| No log        | 85.0  | 340  | 4.7338          |
| No log        | 86.0  | 344  | 4.7337          |
| No log        | 87.0  | 348  | 4.7337          |
| No log        | 88.0  | 352  | 4.7337          |
| No log        | 89.0  | 356  | 4.7336          |
| No log        | 90.0  | 360  | 4.7336          |
| No log        | 91.0  | 364  | 4.7336          |
| No log        | 92.0  | 368  | 4.7336          |
| No log        | 93.0  | 372  | 4.7336          |
| No log        | 94.0  | 376  | 4.7336          |
| No log        | 95.0  | 380  | 4.7336          |
| No log        | 96.0  | 384  | 4.7336          |
| No log        | 97.0  | 388  | 4.7336          |
| No log        | 98.0  | 392  | 4.7336          |
| No log        | 99.0  | 396  | 4.7336          |
| No log        | 100.0 | 400  | 4.7336          |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "distilbert-base-cased-distilled-squad-finetuned-lr1e-08-epochs100", "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-cased-distilled-squad-finetuned-lr1e-08-epochs100
=================================================================


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


* Loss: 4.7336


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-08
* 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: 100


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-08
* 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: 100 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
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: 1e-08
* 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: 100 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
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: 1e-08
* 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: 100### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3