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# distilbert-base-uncased-finetuned-legal_data

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: 6.9101

## 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: 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   | 26   | 5.3529          |
| No log        | 2.0   | 52   | 5.4226          |
| No log        | 3.0   | 78   | 5.2550          |
| No log        | 4.0   | 104  | 5.1011          |
| No log        | 5.0   | 130  | 5.1857          |
| No log        | 6.0   | 156  | 5.5119          |
| No log        | 7.0   | 182  | 5.4480          |
| No log        | 8.0   | 208  | 5.6993          |
| No log        | 9.0   | 234  | 5.9614          |
| No log        | 10.0  | 260  | 5.6987          |
| No log        | 11.0  | 286  | 5.6679          |
| No log        | 12.0  | 312  | 5.9850          |
| No log        | 13.0  | 338  | 5.6065          |
| No log        | 14.0  | 364  | 5.3162          |
| No log        | 15.0  | 390  | 5.7856          |
| No log        | 16.0  | 416  | 5.5786          |
| No log        | 17.0  | 442  | 5.6028          |
| No log        | 18.0  | 468  | 5.7649          |
| No log        | 19.0  | 494  | 5.5382          |
| 1.8345        | 20.0  | 520  | 6.3654          |
| 1.8345        | 21.0  | 546  | 5.3575          |
| 1.8345        | 22.0  | 572  | 5.3808          |
| 1.8345        | 23.0  | 598  | 5.9340          |
| 1.8345        | 24.0  | 624  | 6.1475          |
| 1.8345        | 25.0  | 650  | 6.2188          |
| 1.8345        | 26.0  | 676  | 5.7651          |
| 1.8345        | 27.0  | 702  | 6.2629          |
| 1.8345        | 28.0  | 728  | 6.1356          |
| 1.8345        | 29.0  | 754  | 5.9255          |
| 1.8345        | 30.0  | 780  | 6.4252          |
| 1.8345        | 31.0  | 806  | 5.6967          |
| 1.8345        | 32.0  | 832  | 6.4324          |
| 1.8345        | 33.0  | 858  | 6.5087          |
| 1.8345        | 34.0  | 884  | 6.1113          |
| 1.8345        | 35.0  | 910  | 6.7443          |
| 1.8345        | 36.0  | 936  | 6.6970          |
| 1.8345        | 37.0  | 962  | 6.5578          |
| 1.8345        | 38.0  | 988  | 6.1963          |
| 0.2251        | 39.0  | 1014 | 6.4893          |
| 0.2251        | 40.0  | 1040 | 6.6347          |
| 0.2251        | 41.0  | 1066 | 6.7106          |
| 0.2251        | 42.0  | 1092 | 6.8129          |
| 0.2251        | 43.0  | 1118 | 6.6386          |
| 0.2251        | 44.0  | 1144 | 6.4134          |
| 0.2251        | 45.0  | 1170 | 6.6883          |
| 0.2251        | 46.0  | 1196 | 6.6406          |
| 0.2251        | 47.0  | 1222 | 6.3065          |
| 0.2251        | 48.0  | 1248 | 7.0281          |
| 0.2251        | 49.0  | 1274 | 7.3646          |
| 0.2251        | 50.0  | 1300 | 7.1086          |
| 0.2251        | 51.0  | 1326 | 6.4749          |
| 0.2251        | 52.0  | 1352 | 6.3303          |
| 0.2251        | 53.0  | 1378 | 6.2919          |
| 0.2251        | 54.0  | 1404 | 6.3855          |
| 0.2251        | 55.0  | 1430 | 6.9501          |
| 0.2251        | 56.0  | 1456 | 6.8714          |
| 0.2251        | 57.0  | 1482 | 6.9856          |
| 0.0891        | 58.0  | 1508 | 6.9910          |
| 0.0891        | 59.0  | 1534 | 6.9293          |
| 0.0891        | 60.0  | 1560 | 7.3493          |
| 0.0891        | 61.0  | 1586 | 7.1834          |
| 0.0891        | 62.0  | 1612 | 7.0479          |
| 0.0891        | 63.0  | 1638 | 6.7674          |
| 0.0891        | 64.0  | 1664 | 6.7553          |
| 0.0891        | 65.0  | 1690 | 7.3074          |
| 0.0891        | 66.0  | 1716 | 6.8071          |
| 0.0891        | 67.0  | 1742 | 7.6622          |
| 0.0891        | 68.0  | 1768 | 6.9555          |
| 0.0891        | 69.0  | 1794 | 7.0153          |
| 0.0891        | 70.0  | 1820 | 7.2085          |
| 0.0891        | 71.0  | 1846 | 6.7582          |
| 0.0891        | 72.0  | 1872 | 6.7989          |
| 0.0891        | 73.0  | 1898 | 6.7012          |
| 0.0891        | 74.0  | 1924 | 7.0088          |
| 0.0891        | 75.0  | 1950 | 7.1024          |
| 0.0891        | 76.0  | 1976 | 6.6968          |
| 0.058         | 77.0  | 2002 | 7.5249          |
| 0.058         | 78.0  | 2028 | 6.9199          |
| 0.058         | 79.0  | 2054 | 7.1995          |
| 0.058         | 80.0  | 2080 | 6.9349          |
| 0.058         | 81.0  | 2106 | 7.4025          |
| 0.058         | 82.0  | 2132 | 7.4199          |
| 0.058         | 83.0  | 2158 | 6.8081          |
| 0.058         | 84.0  | 2184 | 7.4777          |
| 0.058         | 85.0  | 2210 | 7.1990          |
| 0.058         | 86.0  | 2236 | 7.0062          |
| 0.058         | 87.0  | 2262 | 7.5724          |
| 0.058         | 88.0  | 2288 | 6.9362          |
| 0.058         | 89.0  | 2314 | 7.1368          |
| 0.058         | 90.0  | 2340 | 7.2183          |
| 0.058         | 91.0  | 2366 | 6.8684          |
| 0.058         | 92.0  | 2392 | 7.1433          |
| 0.058         | 93.0  | 2418 | 7.2161          |
| 0.058         | 94.0  | 2444 | 7.1442          |
| 0.058         | 95.0  | 2470 | 7.3098          |
| 0.058         | 96.0  | 2496 | 7.1264          |
| 0.0512        | 97.0  | 2522 | 6.9424          |
| 0.0512        | 98.0  | 2548 | 6.9155          |
| 0.0512        | 99.0  | 2574 | 6.9038          |
| 0.0512        | 100.0 | 2600 | 6.9101          |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "distilbert-base-uncased-finetuned-legal_data", "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-legal\_data
=============================================


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: 6.9101


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: 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 4.11.3
* Pytorch 1.9.0+cu102
* Datasets 1.12.1
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 100 ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0+cu102
* Datasets 1.12.1
* Tokenizers 0.10.3
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: 2e-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: 100 ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0+cu102
* Datasets 1.12.1
* Tokenizers 0.10.3
passage: 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: 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 4.11.3
* Pytorch 1.9.0+cu102
* Datasets 1.12.1
* Tokenizers 0.10.3