transformers tensorboard safetensors roberta question-answering generated_from_trainer endpoints_compatible region:us
---
tags:
- generated_from_trainer
model-index:
- name: RoBERTa-legal-de-cased_German_legal_SQuAD_part_augmented_100
  results: []
---

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# RoBERTa-legal-de-cased_German_legal_SQuAD_part_augmented_100

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4416

## 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: 128
- 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    | 6.3293          |
| No log        | 2.0   | 8    | 5.8283          |
| No log        | 3.0   | 12   | 5.4334          |
| No log        | 4.0   | 16   | 5.2429          |
| No log        | 5.0   | 20   | 4.8669          |
| No log        | 6.0   | 24   | 4.4701          |
| No log        | 7.0   | 28   | 4.2297          |
| No log        | 8.0   | 32   | 4.0554          |
| No log        | 9.0   | 36   | 3.8815          |
| No log        | 10.0  | 40   | 3.5843          |
| No log        | 11.0  | 44   | 3.4729          |
| No log        | 12.0  | 48   | 3.3379          |
| No log        | 13.0  | 52   | 3.2303          |
| No log        | 14.0  | 56   | 3.1452          |
| No log        | 15.0  | 60   | 3.1223          |
| No log        | 16.0  | 64   | 3.0092          |
| No log        | 17.0  | 68   | 2.9536          |
| No log        | 18.0  | 72   | 2.8647          |
| No log        | 19.0  | 76   | 2.8753          |
| No log        | 20.0  | 80   | 2.7204          |
| No log        | 21.0  | 84   | 2.7557          |
| No log        | 22.0  | 88   | 2.6483          |
| No log        | 23.0  | 92   | 2.5275          |
| No log        | 24.0  | 96   | 2.4505          |
| No log        | 25.0  | 100  | 2.4847          |
| No log        | 26.0  | 104  | 2.3516          |
| No log        | 27.0  | 108  | 2.2191          |
| No log        | 28.0  | 112  | 2.1020          |
| No log        | 29.0  | 116  | 2.1386          |
| No log        | 30.0  | 120  | 2.1153          |
| No log        | 31.0  | 124  | 2.0989          |
| No log        | 32.0  | 128  | 1.8817          |
| No log        | 33.0  | 132  | 2.0152          |
| No log        | 34.0  | 136  | 1.8738          |
| No log        | 35.0  | 140  | 1.9045          |
| No log        | 36.0  | 144  | 1.8466          |
| No log        | 37.0  | 148  | 1.7499          |
| No log        | 38.0  | 152  | 1.8594          |
| No log        | 39.0  | 156  | 1.7723          |
| No log        | 40.0  | 160  | 1.8203          |
| No log        | 41.0  | 164  | 1.7684          |
| No log        | 42.0  | 168  | 1.5812          |
| No log        | 43.0  | 172  | 1.7550          |
| No log        | 44.0  | 176  | 1.6747          |
| No log        | 45.0  | 180  | 1.6487          |
| No log        | 46.0  | 184  | 1.6728          |
| No log        | 47.0  | 188  | 1.6955          |
| No log        | 48.0  | 192  | 1.6211          |
| No log        | 49.0  | 196  | 1.6070          |
| No log        | 50.0  | 200  | 1.6091          |
| No log        | 51.0  | 204  | 1.5952          |
| No log        | 52.0  | 208  | 1.4647          |
| No log        | 53.0  | 212  | 1.4744          |
| No log        | 54.0  | 216  | 1.5051          |
| No log        | 55.0  | 220  | 1.6146          |
| No log        | 56.0  | 224  | 1.5492          |
| No log        | 57.0  | 228  | 1.5286          |
| No log        | 58.0  | 232  | 1.4871          |
| No log        | 59.0  | 236  | 1.5580          |
| No log        | 60.0  | 240  | 1.5212          |
| No log        | 61.0  | 244  | 1.5157          |
| No log        | 62.0  | 248  | 1.5376          |
| No log        | 63.0  | 252  | 1.4648          |
| No log        | 64.0  | 256  | 1.4697          |
| No log        | 65.0  | 260  | 1.5025          |
| No log        | 66.0  | 264  | 1.4722          |
| No log        | 67.0  | 268  | 1.4684          |
| No log        | 68.0  | 272  | 1.5077          |
| No log        | 69.0  | 276  | 1.4737          |
| No log        | 70.0  | 280  | 1.4310          |
| No log        | 71.0  | 284  | 1.4161          |
| No log        | 72.0  | 288  | 1.4315          |
| No log        | 73.0  | 292  | 1.4474          |
| No log        | 74.0  | 296  | 1.4604          |
| No log        | 75.0  | 300  | 1.4644          |
| No log        | 76.0  | 304  | 1.4635          |
| No log        | 77.0  | 308  | 1.4333          |
| No log        | 78.0  | 312  | 1.4232          |
| No log        | 79.0  | 316  | 1.4252          |
| No log        | 80.0  | 320  | 1.3964          |
| No log        | 81.0  | 324  | 1.4254          |
| No log        | 82.0  | 328  | 1.4752          |
| No log        | 83.0  | 332  | 1.4613          |
| No log        | 84.0  | 336  | 1.4674          |
| No log        | 85.0  | 340  | 1.4754          |
| No log        | 86.0  | 344  | 1.4524          |
| No log        | 87.0  | 348  | 1.4367          |
| No log        | 88.0  | 352  | 1.4257          |
| No log        | 89.0  | 356  | 1.4236          |
| No log        | 90.0  | 360  | 1.4267          |
| No log        | 91.0  | 364  | 1.4198          |
| No log        | 92.0  | 368  | 1.4161          |
| No log        | 93.0  | 372  | 1.4145          |
| No log        | 94.0  | 376  | 1.4210          |
| No log        | 95.0  | 380  | 1.4262          |
| No log        | 96.0  | 384  | 1.4376          |
| No log        | 97.0  | 388  | 1.4432          |
| No log        | 98.0  | 392  | 1.4451          |
| No log        | 99.0  | 396  | 1.4436          |
| No log        | 100.0 | 400  | 1.4416          |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.7
- Tokenizers 0.15.0
