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# distilbert-base-cased-distilled-squad-finetuned-lr3e-06-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: 3.3462

## 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: 3e-06
- 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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 9    | 3.0777          |
| No log        | 2.0   | 18   | 3.1319          |
| No log        | 3.0   | 27   | 3.1694          |
| No log        | 4.0   | 36   | 3.0616          |
| No log        | 5.0   | 45   | 3.1448          |
| No log        | 6.0   | 54   | 3.1118          |
| No log        | 7.0   | 63   | 2.9115          |
| No log        | 8.0   | 72   | 2.8013          |
| No log        | 9.0   | 81   | 3.2407          |
| No log        | 10.0  | 90   | 3.2540          |
| No log        | 11.0  | 99   | 3.2567          |
| No log        | 12.0  | 108  | 3.2652          |
| No log        | 13.0  | 117  | 3.2635          |
| No log        | 14.0  | 126  | 3.2646          |
| No log        | 15.0  | 135  | 3.2717          |
| No log        | 16.0  | 144  | 3.2749          |
| No log        | 17.0  | 153  | 3.2778          |
| No log        | 18.0  | 162  | 3.2802          |
| No log        | 19.0  | 171  | 3.2908          |
| No log        | 20.0  | 180  | 3.2998          |
| No log        | 21.0  | 189  | 3.2963          |
| No log        | 22.0  | 198  | 3.2936          |
| No log        | 23.0  | 207  | 3.3001          |
| No log        | 24.0  | 216  | 3.3034          |
| No log        | 25.0  | 225  | 3.3164          |
| No log        | 26.0  | 234  | 3.3119          |
| No log        | 27.0  | 243  | 3.2937          |
| No log        | 28.0  | 252  | 3.2761          |
| No log        | 29.0  | 261  | 3.2692          |
| No log        | 30.0  | 270  | 3.2687          |
| No log        | 31.0  | 279  | 3.3021          |
| No log        | 32.0  | 288  | 3.3296          |
| No log        | 33.0  | 297  | 3.3427          |
| No log        | 34.0  | 306  | 3.3303          |
| No log        | 35.0  | 315  | 3.3177          |
| No log        | 36.0  | 324  | 3.2875          |
| No log        | 37.0  | 333  | 3.2566          |
| No log        | 38.0  | 342  | 3.2476          |
| No log        | 39.0  | 351  | 3.2495          |
| No log        | 40.0  | 360  | 3.2710          |
| No log        | 41.0  | 369  | 3.2782          |
| No log        | 42.0  | 378  | 3.2670          |
| No log        | 43.0  | 387  | 3.2743          |
| No log        | 44.0  | 396  | 3.3123          |
| No log        | 45.0  | 405  | 3.3308          |
| No log        | 46.0  | 414  | 3.3599          |
| No log        | 47.0  | 423  | 3.2345          |
| No log        | 48.0  | 432  | 3.1899          |
| No log        | 49.0  | 441  | 3.2649          |
| No log        | 50.0  | 450  | 3.3745          |
| No log        | 51.0  | 459  | 3.3841          |
| No log        | 52.0  | 468  | 3.3477          |
| No log        | 53.0  | 477  | 3.4445          |
| No log        | 54.0  | 486  | 3.5382          |
| No log        | 55.0  | 495  | 3.5705          |
| 0.0001        | 56.0  | 504  | 3.5022          |
| 0.0001        | 57.0  | 513  | 3.4424          |
| 0.0001        | 58.0  | 522  | 3.4941          |
| 0.0001        | 59.0  | 531  | 3.4784          |
| 0.0001        | 60.0  | 540  | 3.4759          |
| 0.0001        | 61.0  | 549  | 3.4902          |
| 0.0001        | 62.0  | 558  | 3.4874          |
| 0.0001        | 63.0  | 567  | 3.4836          |
| 0.0001        | 64.0  | 576  | 3.4769          |
| 0.0001        | 65.0  | 585  | 3.4762          |
| 0.0001        | 66.0  | 594  | 3.4609          |
| 0.0001        | 67.0  | 603  | 3.4599          |
| 0.0001        | 68.0  | 612  | 3.4530          |
| 0.0001        | 69.0  | 621  | 3.4525          |
| 0.0001        | 70.0  | 630  | 3.4634          |
| 0.0001        | 71.0  | 639  | 3.5287          |
| 0.0001        | 72.0  | 648  | 3.5306          |
| 0.0001        | 73.0  | 657  | 3.5194          |
| 0.0001        | 74.0  | 666  | 3.5239          |
| 0.0001        | 75.0  | 675  | 3.5213          |
| 0.0001        | 76.0  | 684  | 3.4864          |
| 0.0001        | 77.0  | 693  | 3.4199          |
| 0.0001        | 78.0  | 702  | 3.3633          |
| 0.0001        | 79.0  | 711  | 3.3121          |
| 0.0001        | 80.0  | 720  | 3.2907          |
| 0.0001        | 81.0  | 729  | 3.3259          |
| 0.0001        | 82.0  | 738  | 3.3401          |
| 0.0001        | 83.0  | 747  | 3.3613          |
| 0.0001        | 84.0  | 756  | 3.3617          |
| 0.0001        | 85.0  | 765  | 3.3348          |
| 0.0001        | 86.0  | 774  | 3.2861          |
| 0.0001        | 87.0  | 783  | 3.2698          |
| 0.0001        | 88.0  | 792  | 3.3305          |
| 0.0001        | 89.0  | 801  | 3.3725          |
| 0.0001        | 90.0  | 810  | 3.3847          |
| 0.0001        | 91.0  | 819  | 3.3876          |
| 0.0001        | 92.0  | 828  | 3.3788          |
| 0.0001        | 93.0  | 837  | 3.3743          |
| 0.0001        | 94.0  | 846  | 3.3662          |
| 0.0001        | 95.0  | 855  | 3.3581          |
| 0.0001        | 96.0  | 864  | 3.3527          |
| 0.0001        | 97.0  | 873  | 3.3489          |
| 0.0001        | 98.0  | 882  | 3.3471          |
| 0.0001        | 99.0  | 891  | 3.3463          |
| 0.0001        | 100.0 | 900  | 3.3462          |


### 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-lr3e-06-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-lr3e-06-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: 3.3462


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: 3e-06
* 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: 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: 3e-06
* 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: 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: 3e-06
* 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: 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: 3e-06
* 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: 100### Training results### Framework versions


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