
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# finetuned-marktextepoch-n200

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0880

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 200

### Training results

| Training Loss | Epoch | Step   | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 2.5742        | 1.0   | 1606   | 2.4071          |
| 2.4441        | 2.0   | 3212   | 2.2715          |
| 2.3699        | 3.0   | 4818   | 2.2896          |
| 2.3074        | 4.0   | 6424   | 2.2295          |
| 2.2667        | 5.0   | 8030   | 2.2147          |
| 2.2376        | 6.0   | 9636   | 2.1886          |
| 2.2161        | 7.0   | 11242  | 2.1816          |
| 2.1611        | 8.0   | 12848  | 2.1690          |
| 2.1418        | 9.0   | 14454  | 2.1541          |
| 2.1198        | 10.0  | 16060  | 2.1355          |
| 2.1033        | 11.0  | 17666  | 2.1132          |
| 2.0738        | 12.0  | 19272  | 2.1441          |
| 2.0581        | 13.0  | 20878  | 2.1068          |
| 2.0555        | 14.0  | 22484  | 2.1035          |
| 2.0375        | 15.0  | 24090  | 2.1000          |
| 2.0071        | 16.0  | 25696  | 2.1084          |
| 1.9942        | 17.0  | 27302  | 2.0711          |
| 1.9554        | 18.0  | 28908  | 2.0978          |
| 1.9469        | 19.0  | 30514  | 2.0705          |
| 1.9414        | 20.0  | 32120  | 2.0597          |
| 1.9331        | 21.0  | 33726  | 2.0782          |
| 1.9132        | 22.0  | 35332  | 2.0622          |
| 1.9003        | 23.0  | 36938  | 2.0426          |
| 1.9019        | 24.0  | 38544  | 2.0562          |
| 1.8733        | 25.0  | 40150  | 2.0419          |
| 1.8556        | 26.0  | 41756  | 2.0572          |
| 1.8399        | 27.0  | 43362  | 2.0453          |
| 1.8332        | 28.0  | 44968  | 2.0517          |
| 1.8296        | 29.0  | 46574  | 2.0580          |
| 1.788         | 30.0  | 48180  | 2.0454          |
| 1.7944        | 31.0  | 49786  | 2.0193          |
| 1.7716        | 32.0  | 51392  | 2.0595          |
| 1.7799        | 33.0  | 52998  | 2.0379          |
| 1.7633        | 34.0  | 54604  | 2.0392          |
| 1.7477        | 35.0  | 56210  | 2.0122          |
| 1.7407        | 36.0  | 57816  | 2.0293          |
| 1.7163        | 37.0  | 59422  | 2.0339          |
| 1.72          | 38.0  | 61028  | 1.9987          |
| 1.729         | 39.0  | 62634  | 2.0135          |
| 1.709         | 40.0  | 64240  | 2.0455          |
| 1.7019        | 41.0  | 65846  | 2.0206          |
| 1.6958        | 42.0  | 67452  | 2.0408          |
| 1.6789        | 43.0  | 69058  | 2.0470          |
| 1.6907        | 44.0  | 70664  | 2.0280          |
| 1.6531        | 45.0  | 72270  | 2.0514          |
| 1.6563        | 46.0  | 73876  | 2.0428          |
| 1.6364        | 47.0  | 75482  | 2.0305          |
| 1.6534        | 48.0  | 77088  | 2.0200          |
| 1.6312        | 49.0  | 78694  | 2.0444          |
| 1.6092        | 50.0  | 80300  | 2.0154          |
| 1.5998        | 51.0  | 81906  | 2.0249          |
| 1.5808        | 52.0  | 83512  | 2.0235          |
| 1.5945        | 53.0  | 85118  | 2.0286          |
| 1.6004        | 54.0  | 86724  | 2.0288          |
| 1.5802        | 55.0  | 88330  | 2.0346          |
| 1.5665        | 56.0  | 89936  | 2.0120          |
| 1.5723        | 57.0  | 91542  | 2.0257          |
| 1.5553        | 58.0  | 93148  | 2.0146          |
| 1.5445        | 59.0  | 94754  | 2.0333          |
| 1.5669        | 60.0  | 96360  | 2.0325          |
| 1.5318        | 61.0  | 97966  | 2.0250          |
| 1.5117        | 62.0  | 99572  | 2.0343          |
| 1.5248        | 63.0  | 101178 | 2.0183          |
| 1.5149        | 64.0  | 102784 | 2.0422          |
| 1.5087        | 65.0  | 104390 | 2.0236          |
| 1.5087        | 66.0  | 105996 | 2.0275          |
| 1.4938        | 67.0  | 107602 | 2.0384          |
| 1.5008        | 68.0  | 109208 | 2.0167          |
| 1.4871        | 69.0  | 110814 | 2.0456          |
| 1.4931        | 70.0  | 112420 | 2.0083          |
| 1.467         | 71.0  | 114026 | 2.0313          |
| 1.4519        | 72.0  | 115632 | 2.0254          |
| 1.448         | 73.0  | 117238 | 2.0289          |
| 1.4475        | 74.0  | 118844 | 2.0051          |
| 1.4522        | 75.0  | 120450 | 2.0378          |
| 1.4508        | 76.0  | 122056 | 2.0612          |
| 1.4428        | 77.0  | 123662 | 2.0479          |
| 1.4496        | 78.0  | 125268 | 2.0082          |
| 1.4305        | 79.0  | 126874 | 2.0376          |
| 1.4072        | 80.0  | 128480 | 2.0294          |
| 1.4148        | 81.0  | 130086 | 2.0565          |
| 1.4078        | 82.0  | 131692 | 2.0309          |
| 1.3931        | 83.0  | 133298 | 2.0371          |
| 1.4038        | 84.0  | 134904 | 2.0318          |
| 1.3893        | 85.0  | 136510 | 2.0413          |
| 1.3862        | 86.0  | 138116 | 2.0503          |
| 1.3782        | 87.0  | 139722 | 2.0182          |
| 1.3757        | 88.0  | 141328 | 2.0253          |
| 1.3879        | 89.0  | 142934 | 2.0357          |
| 1.3768        | 90.0  | 144540 | 2.0405          |
| 1.3494        | 91.0  | 146146 | 2.0495          |
| 1.3492        | 92.0  | 147752 | 2.0586          |
| 1.353         | 93.0  | 149358 | 2.0779          |
| 1.3397        | 94.0  | 150964 | 2.0564          |
| 1.3486        | 95.0  | 152570 | 2.0459          |
| 1.3262        | 96.0  | 154176 | 2.0692          |
| 1.349         | 97.0  | 155782 | 2.0765          |
| 1.3228        | 98.0  | 157388 | 2.0443          |
| 1.3291        | 99.0  | 158994 | 2.0617          |
| 1.3211        | 100.0 | 160600 | 2.0552          |
| 1.3344        | 101.0 | 162206 | 2.0626          |
| 1.307         | 102.0 | 163812 | 2.0492          |
| 1.2968        | 103.0 | 165418 | 2.0461          |
| 1.2919        | 104.0 | 167024 | 2.0725          |
| 1.3004        | 105.0 | 168630 | 2.0424          |
| 1.303         | 106.0 | 170236 | 2.0484          |
| 1.2847        | 107.0 | 171842 | 2.0083          |
| 1.2861        | 108.0 | 173448 | 2.0491          |
| 1.2763        | 109.0 | 175054 | 2.0505          |
| 1.2852        | 110.0 | 176660 | 2.0691          |
| 1.2611        | 111.0 | 178266 | 2.0711          |
| 1.2739        | 112.0 | 179872 | 2.0730          |
| 1.278         | 113.0 | 181478 | 2.0551          |
| 1.2581        | 114.0 | 183084 | 2.0554          |
| 1.2532        | 115.0 | 184690 | 2.0513          |
| 1.2322        | 116.0 | 186296 | 2.0292          |
| 1.2774        | 117.0 | 187902 | 2.0409          |
| 1.242         | 118.0 | 189508 | 2.0517          |
| 1.2476        | 119.0 | 191114 | 2.0612          |
| 1.2314        | 120.0 | 192720 | 2.0795          |
| 1.2379        | 121.0 | 194326 | 2.0679          |
| 1.2291        | 122.0 | 195932 | 2.0472          |
| 1.2515        | 123.0 | 197538 | 2.0829          |
| 1.2467        | 124.0 | 199144 | 2.0662          |
| 1.2437        | 125.0 | 200750 | 2.0962          |
| 1.2373        | 126.0 | 202356 | 2.0692          |
| 1.2099        | 127.0 | 203962 | 2.0688          |
| 1.1911        | 128.0 | 205568 | 2.0803          |
| 1.2311        | 129.0 | 207174 | 2.0765          |
| 1.2095        | 130.0 | 208780 | 2.0697          |
| 1.2093        | 131.0 | 210386 | 2.0507          |
| 1.2065        | 132.0 | 211992 | 2.0658          |
| 1.1964        | 133.0 | 213598 | 2.0542          |
| 1.2085        | 134.0 | 215204 | 2.0722          |
| 1.1871        | 135.0 | 216810 | 2.0806          |
| 1.1863        | 136.0 | 218416 | 2.0691          |
| 1.1763        | 137.0 | 220022 | 2.0869          |
| 1.1816        | 138.0 | 221628 | 2.0780          |
| 1.1854        | 139.0 | 223234 | 2.0462          |
| 1.1902        | 140.0 | 224840 | 2.0880          |
| 1.1762        | 141.0 | 226446 | 2.0682          |
| 1.1551        | 142.0 | 228052 | 2.0837          |
| 1.171         | 143.0 | 229658 | 2.1028          |
| 1.1571        | 144.0 | 231264 | 2.0726          |
| 1.1627        | 145.0 | 232870 | 2.0863          |
| 1.1537        | 146.0 | 234476 | 2.0857          |
| 1.1695        | 147.0 | 236082 | 2.0620          |
| 1.1477        | 148.0 | 237688 | 2.0817          |
| 1.1592        | 149.0 | 239294 | 2.0705          |
| 1.1478        | 150.0 | 240900 | 2.0841          |
| 1.1398        | 151.0 | 242506 | 2.0886          |
| 1.144         | 152.0 | 244112 | 2.0673          |
| 1.1646        | 153.0 | 245718 | 2.0620          |
| 1.12          | 154.0 | 247324 | 2.0821          |
| 1.1419        | 155.0 | 248930 | 2.0632          |
| 1.1436        | 156.0 | 250536 | 2.0817          |
| 1.1365        | 157.0 | 252142 | 2.0663          |
| 1.1318        | 158.0 | 253748 | 2.0796          |
| 1.1219        | 159.0 | 255354 | 2.0825          |
| 1.1306        | 160.0 | 256960 | 2.0837          |
| 1.1295        | 161.0 | 258566 | 2.0564          |
| 1.1261        | 162.0 | 260172 | 2.0722          |
| 1.1273        | 163.0 | 261778 | 2.1058          |
| 1.1143        | 164.0 | 263384 | 2.0963          |
| 1.1276        | 165.0 | 264990 | 2.0948          |
| 1.1238        | 166.0 | 266596 | 2.0695          |
| 1.1222        | 167.0 | 268202 | 2.0801          |
| 1.1145        | 168.0 | 269808 | 2.0768          |
| 1.1093        | 169.0 | 271414 | 2.0664          |
| 1.1141        | 170.0 | 273020 | 2.0903          |
| 1.0936        | 171.0 | 274626 | 2.1012          |
| 1.1048        | 172.0 | 276232 | 2.1033          |
| 1.0991        | 173.0 | 277838 | 2.0761          |
| 1.1164        | 174.0 | 279444 | 2.0689          |
| 1.0935        | 175.0 | 281050 | 2.0754          |
| 1.1032        | 176.0 | 282656 | 2.0810          |
| 1.1124        | 177.0 | 284262 | 2.0790          |
| 1.1107        | 178.0 | 285868 | 2.0762          |
| 1.085         | 179.0 | 287474 | 2.0697          |
| 1.093         | 180.0 | 289080 | 2.0856          |
| 1.1034        | 181.0 | 290686 | 2.0734          |
| 1.0983        | 182.0 | 292292 | 2.0837          |
| 1.0972        | 183.0 | 293898 | 2.1063          |
| 1.0909        | 184.0 | 295504 | 2.0873          |
| 1.0805        | 185.0 | 297110 | 2.0888          |
| 1.0893        | 186.0 | 298716 | 2.0498          |
| 1.096         | 187.0 | 300322 | 2.0906          |
| 1.0781        | 188.0 | 301928 | 2.0905          |
| 1.0981        | 189.0 | 303534 | 2.0767          |
| 1.093         | 190.0 | 305140 | 2.0695          |
| 1.0814        | 191.0 | 306746 | 2.0763          |
| 1.0862        | 192.0 | 308352 | 2.0890          |
| 1.0833        | 193.0 | 309958 | 2.1026          |
| 1.0806        | 194.0 | 311564 | 2.0978          |
| 1.0834        | 195.0 | 313170 | 2.1004          |
| 1.0807        | 196.0 | 314776 | 2.0953          |
| 1.0827        | 197.0 | 316382 | 2.1129          |
| 1.0826        | 198.0 | 317988 | 2.1069          |
| 1.0796        | 199.0 | 319594 | 2.0867          |
| 1.0881        | 200.0 | 321200 | 2.0880          |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "finetuned-marktextepoch-n200", "results": []}]}
transformers pytorch tensorboard roberta fill-mask generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

finetuned-marktextepoch-n200
============================


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


* Loss: 2.0880


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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 200


### Training results



### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 200 ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #roberta #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 200 ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #roberta #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 200### Training results### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1