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# nl_electra

This model is a pretrained version of [ELECTRA](https://huggingface.co/docs/transformers/model_doc/electra) on the Dutch subset of the [CC100](https://huggingface.co/datasets/cc100) dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4650
- Accuracy: 0.5392

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 703
- gradient_accumulation_steps: 32
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 8000
- num_epochs: 400.0

### Training results

| Training Loss | Epoch  | Step   | Validation Loss | Accuracy |
|:-------------:|:------:|:------:|:---------------:|:--------:|
| No log        | 0.67   | 500    | 9.9977          | 0.0486   |
| No log        | 1.35   | 1000   | 9.5620          | 0.0543   |
| No log        | 2.02   | 1500   | 8.9306          | 0.0741   |
| No log        | 2.69   | 2000   | 8.2617          | 0.0826   |
| No log        | 3.36   | 2500   | 7.6880          | 0.0792   |
| No log        | 4.04   | 3000   | 7.3316          | 0.0757   |
| No log        | 4.71   | 3500   | 7.1944          | 0.0747   |
| No log        | 5.38   | 4000   | 7.1349          | 0.0802   |
| No log        | 6.06   | 4500   | 7.0752          | 0.0887   |
| 8.201         | 6.73   | 5000   | 7.0046          | 0.1021   |
| 8.201         | 7.4    | 5500   | 6.9295          | 0.1090   |
| 8.201         | 8.08   | 6000   | 6.8483          | 0.1132   |
| 8.201         | 8.75   | 6500   | 6.7750          | 0.1171   |
| 8.201         | 9.42   | 7000   | 6.7116          | 0.1187   |
| 8.201         | 10.09  | 7500   | 6.6560          | 0.1218   |
| 8.201         | 10.77  | 8000   | 6.6178          | 0.1239   |
| 8.201         | 11.44  | 8500   | 6.5824          | 0.1255   |
| 8.201         | 12.11  | 9000   | 6.5521          | 0.1273   |
| 8.201         | 12.79  | 9500   | 6.5203          | 0.1292   |
| 6.7257        | 13.46  | 10000  | 6.5027          | 0.1303   |
| 6.7257        | 14.13  | 10500  | 6.4809          | 0.1314   |
| 6.7257        | 14.8   | 11000  | 6.4631          | 0.1322   |
| 6.7257        | 15.48  | 11500  | 6.4483          | 0.1329   |
| 6.7257        | 16.15  | 12000  | 6.4320          | 0.1338   |
| 6.7257        | 16.82  | 12500  | 6.4169          | 0.1348   |
| 6.7257        | 17.5   | 13000  | 6.4067          | 0.1359   |
| 6.7257        | 18.17  | 13500  | 6.3994          | 0.1359   |
| 6.7257        | 18.84  | 14000  | 6.3823          | 0.1368   |
| 6.7257        | 19.52  | 14500  | 6.3759          | 0.1373   |
| 6.4502        | 20.19  | 15000  | 6.3629          | 0.1374   |
| 6.4502        | 20.86  | 15500  | 6.3638          | 0.1373   |
| 6.4502        | 21.53  | 16000  | 6.3505          | 0.1382   |
| 6.4502        | 22.21  | 16500  | 6.3416          | 0.1387   |
| 6.4502        | 22.88  | 17000  | 6.3420          | 0.1383   |
| 6.4502        | 23.55  | 17500  | 6.3330          | 0.1389   |
| 6.4502        | 24.23  | 18000  | 6.3289          | 0.1388   |
| 6.4502        | 24.9   | 18500  | 6.3184          | 0.1389   |
| 6.4502        | 25.57  | 19000  | 6.3099          | 0.1396   |
| 6.4502        | 26.24  | 19500  | 6.2789          | 0.1405   |
| 6.3474        | 26.92  | 20000  | 6.2398          | 0.1404   |
| 6.3474        | 27.59  | 20500  | 6.2012          | 0.1412   |
| 6.3474        | 28.26  | 21000  | 6.1803          | 0.1414   |
| 6.3474        | 28.94  | 21500  | 6.1579          | 0.1414   |
| 6.3474        | 29.61  | 22000  | 6.1403          | 0.1431   |
| 6.3474        | 30.28  | 22500  | 6.1316          | 0.1423   |
| 6.3474        | 30.96  | 23000  | 6.1102          | 0.1435   |
| 6.3474        | 31.63  | 23500  | 6.0998          | 0.1439   |
| 6.3474        | 32.3   | 24000  | 6.0867          | 0.1446   |
| 6.3474        | 32.97  | 24500  | 6.0700          | 0.1451   |
| 6.1758        | 33.65  | 25000  | 6.0554          | 0.1457   |
| 6.1758        | 34.32  | 25500  | 6.0487          | 0.1457   |
| 6.1758        | 34.99  | 26000  | 6.0328          | 0.1469   |
| 6.1758        | 35.67  | 26500  | 6.0265          | 0.1469   |
| 6.1758        | 36.34  | 27000  | 5.9992          | 0.1486   |
| 6.1758        | 37.01  | 27500  | 5.9934          | 0.1485   |
| 6.1758        | 37.68  | 28000  | 5.9702          | 0.1501   |
| 6.1758        | 38.36  | 28500  | 5.9661          | 0.1503   |
| 6.1758        | 39.03  | 29000  | 5.9558          | 0.1512   |
| 6.1758        | 39.7   | 29500  | 5.9321          | 0.1528   |
| 6.052         | 40.38  | 30000  | 5.9147          | 0.1532   |
| 6.052         | 41.05  | 30500  | 5.8975          | 0.1545   |
| 6.052         | 41.72  | 31000  | 5.8784          | 0.1566   |
| 6.052         | 42.4   | 31500  | 5.8584          | 0.1586   |
| 6.052         | 43.07  | 32000  | 5.8325          | 0.1603   |
| 6.052         | 43.74  | 32500  | 5.7583          | 0.1664   |
| 6.052         | 44.41  | 33000  | 5.6158          | 0.1787   |
| 6.052         | 45.09  | 33500  | 5.4580          | 0.1917   |
| 6.052         | 45.76  | 34000  | 5.3396          | 0.2010   |
| 6.052         | 46.43  | 34500  | 5.2568          | 0.2082   |
| 5.7995        | 47.11  | 35000  | 5.1775          | 0.2146   |
| 5.7995        | 47.78  | 35500  | 5.1076          | 0.2204   |
| 5.7995        | 48.45  | 36000  | 5.0457          | 0.2258   |
| 5.7995        | 49.13  | 36500  | 4.9932          | 0.2313   |
| 5.7995        | 49.8   | 37000  | 4.9164          | 0.2384   |
| 5.7995        | 50.47  | 37500  | 4.7844          | 0.2521   |
| 5.7995        | 51.14  | 38000  | 4.6598          | 0.2642   |
| 5.7995        | 51.82  | 38500  | 4.5472          | 0.2757   |
| 5.7995        | 52.49  | 39000  | 4.4374          | 0.2871   |
| 5.7995        | 53.16  | 39500  | 4.3399          | 0.2982   |
| 5.0341        | 53.84  | 40000  | 4.2549          | 0.3083   |
| 5.0341        | 54.51  | 40500  | 4.1795          | 0.3170   |
| 5.0341        | 55.18  | 41000  | 4.1017          | 0.3274   |
| 5.0341        | 55.85  | 41500  | 4.0308          | 0.3375   |
| 5.0341        | 56.53  | 42000  | 3.9673          | 0.3462   |
| 5.0341        | 57.2   | 42500  | 3.9130          | 0.3538   |
| 5.0341        | 57.87  | 43000  | 3.8672          | 0.3599   |
| 5.0341        | 58.55  | 43500  | 3.8249          | 0.3656   |
| 5.0341        | 59.22  | 44000  | 3.7748          | 0.3728   |
| 5.0341        | 59.89  | 44500  | 3.7459          | 0.3768   |
| 4.2119        | 60.57  | 45000  | 3.7089          | 0.3808   |
| 4.2119        | 61.24  | 45500  | 3.6732          | 0.3857   |
| 4.2119        | 61.91  | 46000  | 3.6546          | 0.3881   |
| 4.2119        | 62.58  | 46500  | 3.6205          | 0.3921   |
| 4.2119        | 63.26  | 47000  | 3.5908          | 0.3960   |
| 4.2119        | 63.93  | 47500  | 3.5627          | 0.3991   |
| 4.2119        | 64.6   | 48000  | 3.5466          | 0.4019   |
| 4.2119        | 65.28  | 48500  | 3.5262          | 0.4039   |
| 4.2119        | 65.95  | 49000  | 3.4987          | 0.4074   |
| 4.2119        | 66.62  | 49500  | 3.4817          | 0.4093   |
| 3.8182        | 67.29  | 50000  | 3.4608          | 0.4119   |
| 3.8182        | 67.97  | 50500  | 3.4467          | 0.4142   |
| 3.8182        | 68.64  | 51000  | 3.4280          | 0.4163   |
| 3.8182        | 69.31  | 51500  | 3.4165          | 0.4175   |
| 3.8182        | 69.99  | 52000  | 3.3970          | 0.4199   |
| 3.8182        | 70.66  | 52500  | 3.3738          | 0.4227   |
| 3.8182        | 71.33  | 53000  | 3.3640          | 0.4242   |
| 3.8182        | 72.01  | 53500  | 3.3583          | 0.4252   |
| 3.8182        | 72.68  | 54000  | 3.3319          | 0.4279   |
| 3.8182        | 73.35  | 54500  | 3.3153          | 0.4303   |
| 3.5946        | 74.02  | 55000  | 3.3098          | 0.4304   |
| 3.5946        | 74.7   | 55500  | 3.2949          | 0.4328   |
| 3.5946        | 75.37  | 56000  | 3.2820          | 0.4335   |
| 3.5946        | 76.04  | 56500  | 3.2686          | 0.4355   |
| 3.5946        | 76.72  | 57000  | 3.2663          | 0.4359   |
| 3.5946        | 77.39  | 57500  | 3.2482          | 0.4379   |
| 3.5946        | 78.06  | 58000  | 3.2344          | 0.4393   |
| 3.5946        | 78.73  | 58500  | 3.2281          | 0.4407   |
| 3.5946        | 79.41  | 59000  | 3.2172          | 0.4412   |
| 3.5946        | 80.08  | 59500  | 3.2110          | 0.4420   |
| 3.4435        | 80.75  | 60000  | 3.1940          | 0.4443   |
| 3.4435        | 81.43  | 60500  | 3.1837          | 0.4455   |
| 3.4435        | 82.1   | 61000  | 3.1744          | 0.4469   |
| 3.4435        | 82.77  | 61500  | 3.1611          | 0.4483   |
| 3.4435        | 83.45  | 62000  | 3.1531          | 0.4496   |
| 3.4435        | 84.12  | 62500  | 3.1524          | 0.4499   |
| 3.4435        | 84.79  | 63000  | 3.1431          | 0.4501   |
| 3.4435        | 85.46  | 63500  | 3.1287          | 0.4527   |
| 3.4435        | 86.14  | 64000  | 3.1192          | 0.4533   |
| 3.4435        | 86.81  | 64500  | 3.1107          | 0.4547   |
| 3.3301        | 87.48  | 65000  | 3.1041          | 0.4553   |
| 3.3301        | 88.16  | 65500  | 3.0999          | 0.4562   |
| 3.3301        | 88.83  | 66000  | 3.0882          | 0.4576   |
| 3.3301        | 89.5   | 66500  | 3.0777          | 0.4589   |
| 3.3301        | 90.17  | 67000  | 3.0726          | 0.4588   |
| 3.3301        | 90.85  | 67500  | 3.0676          | 0.4601   |
| 3.3301        | 91.52  | 68000  | 3.0616          | 0.4602   |
| 3.3301        | 92.19  | 68500  | 3.0523          | 0.4621   |
| 3.3301        | 92.87  | 69000  | 3.0464          | 0.4624   |
| 3.3301        | 93.54  | 69500  | 3.0405          | 0.4635   |
| 3.2418        | 94.21  | 70000  | 3.0312          | 0.4649   |
| 3.2418        | 94.89  | 70500  | 3.0209          | 0.4653   |
| 3.2418        | 95.56  | 71000  | 3.0202          | 0.4657   |
| 3.2418        | 96.23  | 71500  | 3.0101          | 0.4676   |
| 3.2418        | 96.9   | 72000  | 3.0105          | 0.4666   |
| 3.2418        | 97.58  | 72500  | 3.0023          | 0.4685   |
| 3.2418        | 98.25  | 73000  | 3.0008          | 0.4680   |
| 3.2418        | 98.92  | 73500  | 2.9882          | 0.4691   |
| 3.2418        | 99.6   | 74000  | 2.9855          | 0.4702   |
| 3.2418        | 100.27 | 74500  | 2.9790          | 0.4709   |
| 3.1698        | 100.94 | 75000  | 2.9680          | 0.4716   |
| 3.1698        | 101.61 | 75500  | 2.9667          | 0.4724   |
| 3.1698        | 102.29 | 76000  | 2.9657          | 0.4726   |
| 3.1698        | 102.96 | 76500  | 2.9623          | 0.4731   |
| 3.1698        | 103.63 | 77000  | 2.9515          | 0.4745   |
| 3.1698        | 104.31 | 77500  | 2.9471          | 0.4753   |
| 3.1698        | 104.98 | 78000  | 2.9407          | 0.4756   |
| 3.1698        | 105.65 | 78500  | 2.9388          | 0.4761   |
| 3.1698        | 106.33 | 79000  | 2.9369          | 0.4766   |
| 3.1698        | 107.0  | 79500  | 2.9297          | 0.4762   |
| 3.1101        | 107.67 | 80000  | 2.9291          | 0.4776   |
| 3.1101        | 108.34 | 80500  | 2.9139          | 0.4788   |
| 3.1101        | 109.02 | 81000  | 2.9113          | 0.4790   |
| 3.1101        | 109.69 | 81500  | 2.9057          | 0.4798   |
| 3.1101        | 110.36 | 82000  | 2.9058          | 0.4804   |
| 3.1101        | 111.04 | 82500  | 2.9019          | 0.4807   |
| 3.1101        | 111.71 | 83000  | 2.8934          | 0.4818   |
| 3.1101        | 112.38 | 83500  | 2.8864          | 0.4825   |
| 3.1101        | 113.06 | 84000  | 2.8926          | 0.4815   |
| 3.1101        | 113.73 | 84500  | 2.8812          | 0.4830   |
| 3.058         | 114.4  | 85000  | 2.8740          | 0.4840   |
| 3.058         | 115.07 | 85500  | 2.8730          | 0.4840   |
| 3.058         | 115.75 | 86000  | 2.8694          | 0.4847   |
| 3.058         | 116.42 | 86500  | 2.8694          | 0.4848   |
| 3.058         | 117.09 | 87000  | 2.8601          | 0.4862   |
| 3.058         | 117.77 | 87500  | 2.8547          | 0.4862   |
| 3.058         | 118.44 | 88000  | 2.8538          | 0.4861   |
| 3.058         | 119.11 | 88500  | 2.8494          | 0.4876   |
| 3.058         | 119.78 | 89000  | 2.8430          | 0.4882   |
| 3.058         | 120.46 | 89500  | 2.8436          | 0.4875   |
| 3.0129        | 121.13 | 90000  | 2.8402          | 0.4884   |
| 3.0129        | 121.8  | 90500  | 2.8353          | 0.4888   |
| 3.0129        | 122.48 | 91000  | 2.8271          | 0.4896   |
| 3.0129        | 123.15 | 91500  | 2.8236          | 0.4900   |
| 3.0129        | 123.82 | 92000  | 2.8199          | 0.4913   |
| 3.0129        | 124.5  | 92500  | 2.8119          | 0.4916   |
| 3.0129        | 125.17 | 93000  | 2.8138          | 0.4916   |
| 3.0129        | 125.84 | 93500  | 2.8089          | 0.4925   |
| 3.0129        | 126.51 | 94000  | 2.8067          | 0.4928   |
| 3.0129        | 127.19 | 94500  | 2.8010          | 0.4939   |
| 2.9701        | 127.86 | 95000  | 2.7992          | 0.4938   |
| 2.9701        | 128.53 | 95500  | 2.7953          | 0.4948   |
| 2.9701        | 129.21 | 96000  | 2.7964          | 0.4942   |
| 2.9701        | 129.88 | 96500  | 2.7838          | 0.4955   |
| 2.9701        | 130.55 | 97000  | 2.7770          | 0.4968   |
| 2.9701        | 131.22 | 97500  | 2.7800          | 0.4962   |
| 2.9701        | 131.9  | 98000  | 2.7743          | 0.4972   |
| 2.9701        | 132.57 | 98500  | 2.7696          | 0.4973   |
| 2.9701        | 133.24 | 99000  | 2.7691          | 0.4980   |
| 2.9701        | 133.92 | 99500  | 2.7612          | 0.4989   |
| 2.9289        | 134.59 | 100000 | 2.7606          | 0.4987   |
| 2.9289        | 135.26 | 100500 | 2.7545          | 0.4993   |
| 2.9289        | 135.94 | 101000 | 2.7544          | 0.4999   |
| 2.9289        | 136.61 | 101500 | 2.7550          | 0.4999   |
| 2.9289        | 137.28 | 102000 | 2.7510          | 0.5001   |
| 2.9289        | 137.95 | 102500 | 2.7480          | 0.5002   |
| 2.9289        | 138.63 | 103000 | 2.7422          | 0.5012   |
| 2.9289        | 139.3  | 103500 | 2.7419          | 0.5014   |
| 2.9289        | 139.97 | 104000 | 2.7416          | 0.5009   |
| 2.9289        | 140.65 | 104500 | 2.7412          | 0.5017   |
| 2.8968        | 141.32 | 105000 | 2.7356          | 0.5023   |
| 2.8968        | 141.99 | 105500 | 2.7303          | 0.5027   |
| 2.8968        | 142.66 | 106000 | 2.7359          | 0.5029   |
| 2.8968        | 143.34 | 106500 | 2.7283          | 0.5032   |
| 2.8968        | 144.01 | 107000 | 2.7226          | 0.5033   |
| 2.8968        | 144.68 | 107500 | 2.7247          | 0.5039   |
| 2.8968        | 145.36 | 108000 | 2.7209          | 0.5044   |
| 2.8968        | 146.03 | 108500 | 2.7210          | 0.5039   |
| 2.8968        | 146.7  | 109000 | 2.7135          | 0.5046   |
| 2.8968        | 147.38 | 109500 | 2.7139          | 0.5048   |
| 2.8697        | 148.05 | 110000 | 2.7167          | 0.5050   |
| 2.8697        | 148.72 | 110500 | 2.7125          | 0.5058   |
| 2.8697        | 149.39 | 111000 | 2.7064          | 0.5060   |
| 2.8697        | 150.07 | 111500 | 2.7024          | 0.5067   |
| 2.8697        | 150.74 | 112000 | 2.7035          | 0.5067   |
| 2.8697        | 151.41 | 112500 | 2.7034          | 0.5067   |
| 2.8697        | 152.09 | 113000 | 2.6967          | 0.5073   |
| 2.8697        | 152.76 | 113500 | 2.6982          | 0.5070   |
| 2.8697        | 153.43 | 114000 | 2.6948          | 0.5079   |
| 2.8697        | 154.1  | 114500 | 2.6946          | 0.5076   |
| 2.8457        | 154.78 | 115000 | 2.6918          | 0.5078   |
| 2.8457        | 155.45 | 115500 | 2.6917          | 0.5078   |
| 2.8457        | 156.12 | 116000 | 2.6868          | 0.5086   |
| 2.8457        | 156.8  | 116500 | 2.6870          | 0.5084   |
| 2.8457        | 157.47 | 117000 | 2.6830          | 0.5091   |
| 2.8457        | 158.14 | 117500 | 2.6824          | 0.5090   |
| 2.8457        | 158.82 | 118000 | 2.6812          | 0.5092   |
| 2.8457        | 159.49 | 118500 | 2.6747          | 0.5098   |
| 2.8457        | 160.16 | 119000 | 2.6747          | 0.5105   |
| 2.8457        | 160.83 | 119500 | 2.6750          | 0.5102   |
| 2.825         | 161.51 | 120000 | 2.6761          | 0.5102   |
| 2.825         | 162.18 | 120500 | 2.6670          | 0.5115   |
| 2.825         | 162.85 | 121000 | 2.6740          | 0.5104   |
| 2.825         | 163.53 | 121500 | 2.6700          | 0.5106   |
| 2.825         | 164.2  | 122000 | 2.6629          | 0.5119   |
| 2.825         | 164.87 | 122500 | 2.6642          | 0.5117   |
| 2.825         | 165.54 | 123000 | 2.6664          | 0.5109   |
| 2.825         | 166.22 | 123500 | 2.6626          | 0.5117   |
| 2.825         | 166.89 | 124000 | 2.6561          | 0.5130   |
| 2.825         | 167.56 | 124500 | 2.6612          | 0.5125   |
| 2.8059        | 168.24 | 125000 | 2.6594          | 0.5123   |
| 2.8059        | 168.91 | 125500 | 2.6508          | 0.5132   |
| 2.8059        | 169.58 | 126000 | 2.6477          | 0.5134   |
| 2.8059        | 170.26 | 126500 | 2.6527          | 0.5133   |
| 2.8059        | 170.93 | 127000 | 2.6519          | 0.5136   |
| 2.8059        | 171.6  | 127500 | 2.6456          | 0.5141   |
| 2.8059        | 172.27 | 128000 | 2.6473          | 0.5139   |
| 2.8059        | 172.95 | 128500 | 2.6426          | 0.5144   |
| 2.8059        | 173.62 | 129000 | 2.6454          | 0.5137   |
| 2.8059        | 174.29 | 129500 | 2.6427          | 0.5147   |
| 2.788         | 174.97 | 130000 | 2.6376          | 0.5150   |
| 2.788         | 175.64 | 130500 | 2.6366          | 0.5154   |
| 2.788         | 176.31 | 131000 | 2.6327          | 0.5156   |
| 2.788         | 176.98 | 131500 | 2.6328          | 0.5157   |
| 2.788         | 177.66 | 132000 | 2.6335          | 0.5156   |
| 2.788         | 178.33 | 132500 | 2.6302          | 0.5166   |
| 2.788         | 179.0  | 133000 | 2.6333          | 0.5160   |
| 2.788         | 179.68 | 133500 | 2.6253          | 0.5171   |
| 2.788         | 180.35 | 134000 | 2.6237          | 0.5167   |
| 2.788         | 181.02 | 134500 | 2.6269          | 0.5165   |
| 2.7723        | 181.7  | 135000 | 2.6283          | 0.5164   |
| 2.7723        | 182.37 | 135500 | 2.6255          | 0.5174   |
| 2.7723        | 183.04 | 136000 | 2.6254          | 0.5175   |
| 2.7723        | 183.71 | 136500 | 2.6231          | 0.5172   |
| 2.7723        | 184.39 | 137000 | 2.6181          | 0.5173   |
| 2.7723        | 185.06 | 137500 | 2.6260          | 0.5168   |
| 2.7723        | 185.73 | 138000 | 2.6183          | 0.5176   |
| 2.7723        | 186.41 | 138500 | 2.6174          | 0.5182   |
| 2.7723        | 187.08 | 139000 | 2.6144          | 0.5182   |
| 2.7723        | 187.75 | 139500 | 2.6152          | 0.5186   |
| 2.7575        | 188.43 | 140000 | 2.6150          | 0.5183   |
| 2.7575        | 189.1  | 140500 | 2.6110          | 0.5190   |
| 2.7575        | 189.77 | 141000 | 2.6044          | 0.5194   |
| 2.7575        | 190.44 | 141500 | 2.6083          | 0.5186   |
| 2.7575        | 191.12 | 142000 | 2.6102          | 0.5189   |
| 2.7575        | 191.79 | 142500 | 2.6063          | 0.5195   |
| 2.7575        | 192.46 | 143000 | 2.6071          | 0.5198   |
| 2.7575        | 193.14 | 143500 | 2.6090          | 0.5191   |
| 2.7575        | 193.81 | 144000 | 2.6068          | 0.5200   |
| 2.7575        | 194.48 | 144500 | 2.6032          | 0.5200   |
| 2.7445        | 195.15 | 145000 | 2.6031          | 0.5200   |
| 2.7445        | 195.83 | 145500 | 2.6007          | 0.5201   |
| 2.7445        | 196.5  | 146000 | 2.5998          | 0.5203   |
| 2.7445        | 197.17 | 146500 | 2.5980          | 0.5208   |
| 2.7445        | 197.85 | 147000 | 2.5952          | 0.5211   |
| 2.7445        | 198.52 | 147500 | 2.5977          | 0.5210   |
| 2.7445        | 199.19 | 148000 | 2.5922          | 0.5212   |
| 2.7445        | 199.87 | 148500 | 2.5936          | 0.5211   |
| 2.7445        | 200.54 | 149000 | 2.5933          | 0.5219   |
| 2.7445        | 201.21 | 149500 | 2.5887          | 0.5219   |
| 2.7324        | 201.88 | 150000 | 2.5911          | 0.5215   |
| 2.7324        | 202.56 | 150500 | 2.5892          | 0.5219   |
| 2.7324        | 203.23 | 151000 | 2.5875          | 0.5218   |
| 2.7324        | 203.9  | 151500 | 2.5898          | 0.5220   |
| 2.7324        | 204.58 | 152000 | 2.5872          | 0.5223   |
| 2.7324        | 205.25 | 152500 | 2.5805          | 0.5226   |
| 2.7324        | 205.92 | 153000 | 2.5861          | 0.5225   |
| 2.7324        | 206.59 | 153500 | 2.5839          | 0.5223   |
| 2.7324        | 207.27 | 154000 | 2.5804          | 0.5232   |
| 2.7324        | 207.94 | 154500 | 2.5766          | 0.5235   |
| 2.7212        | 208.61 | 155000 | 2.5764          | 0.5233   |
| 2.7212        | 209.29 | 155500 | 2.5801          | 0.5233   |
| 2.7212        | 209.96 | 156000 | 2.5737          | 0.5241   |
| 2.7212        | 210.63 | 156500 | 2.5769          | 0.5236   |
| 2.7212        | 211.31 | 157000 | 2.5769          | 0.5237   |
| 2.7212        | 211.98 | 157500 | 2.5748          | 0.5239   |
| 2.7212        | 212.65 | 158000 | 2.5745          | 0.5230   |
| 2.7212        | 213.32 | 158500 | 2.5725          | 0.5240   |
| 2.7212        | 214.0  | 159000 | 2.5736          | 0.5239   |
| 2.7212        | 214.67 | 159500 | 2.5675          | 0.5252   |
| 2.7103        | 215.34 | 160000 | 2.5678          | 0.5245   |
| 2.7103        | 216.02 | 160500 | 2.5691          | 0.5250   |
| 2.7103        | 216.69 | 161000 | 2.5688          | 0.5245   |
| 2.7103        | 217.36 | 161500 | 2.5681          | 0.5251   |
| 2.7103        | 218.03 | 162000 | 2.5582          | 0.5255   |
| 2.7103        | 218.71 | 162500 | 2.5675          | 0.5247   |
| 2.7103        | 219.38 | 163000 | 2.5609          | 0.5259   |
| 2.7103        | 220.05 | 163500 | 2.5625          | 0.5254   |
| 2.7103        | 220.73 | 164000 | 2.5630          | 0.5254   |
| 2.7103        | 221.4  | 164500 | 2.5607          | 0.5265   |
| 2.7003        | 222.07 | 165000 | 2.5615          | 0.5260   |
| 2.7003        | 222.75 | 165500 | 2.5660          | 0.5248   |
| 2.7003        | 223.42 | 166000 | 2.5569          | 0.5263   |
| 2.7003        | 224.09 | 166500 | 2.5610          | 0.5255   |
| 2.7003        | 224.76 | 167000 | 2.5569          | 0.5263   |
| 2.7003        | 225.44 | 167500 | 2.5534          | 0.5265   |
| 2.7003        | 226.11 | 168000 | 2.5573          | 0.5259   |
| 2.7003        | 226.78 | 168500 | 2.5559          | 0.5264   |
| 2.7003        | 227.46 | 169000 | 2.5508          | 0.5277   |
| 2.7003        | 228.13 | 169500 | 2.5500          | 0.5276   |
| 2.6915        | 228.8  | 170000 | 2.5501          | 0.5270   |
| 2.6915        | 229.47 | 170500 | 2.5508          | 0.5273   |
| 2.6915        | 230.15 | 171000 | 2.5523          | 0.5267   |
| 2.6915        | 230.82 | 171500 | 2.5464          | 0.5276   |
| 2.6915        | 231.49 | 172000 | 2.5482          | 0.5271   |
| 2.6915        | 232.17 | 172500 | 2.5486          | 0.5270   |
| 2.6915        | 232.84 | 173000 | 2.5474          | 0.5275   |
| 2.6915        | 233.51 | 173500 | 2.5483          | 0.5270   |
| 2.6915        | 234.19 | 174000 | 2.5480          | 0.5276   |
| 2.6915        | 234.86 | 174500 | 2.5486          | 0.5278   |
| 2.6833        | 235.53 | 175000 | 2.5484          | 0.5273   |
| 2.6833        | 236.2  | 175500 | 2.5436          | 0.5277   |
| 2.6833        | 236.88 | 176000 | 2.5448          | 0.5278   |
| 2.6833        | 237.55 | 176500 | 2.5430          | 0.5284   |
| 2.6833        | 238.22 | 177000 | 2.5433          | 0.5279   |
| 2.6833        | 238.9  | 177500 | 2.5398          | 0.5288   |
| 2.6833        | 239.57 | 178000 | 2.5424          | 0.5282   |
| 2.6833        | 240.24 | 178500 | 2.5371          | 0.5291   |
| 2.6833        | 240.91 | 179000 | 2.5372          | 0.5294   |
| 2.6833        | 241.59 | 179500 | 2.5368          | 0.5290   |
| 2.6753        | 242.26 | 180000 | 2.5383          | 0.5289   |
| 2.6753        | 242.93 | 180500 | 2.5387          | 0.5289   |
| 2.6753        | 243.61 | 181000 | 2.5351          | 0.5295   |
| 2.6753        | 244.28 | 181500 | 2.5340          | 0.5296   |
| 2.6753        | 244.95 | 182000 | 2.5349          | 0.5289   |
| 2.6753        | 245.63 | 182500 | 2.5358          | 0.5295   |
| 2.6753        | 246.3  | 183000 | 2.5333          | 0.5299   |
| 2.6753        | 246.97 | 183500 | 2.5363          | 0.5292   |
| 2.6753        | 247.64 | 184000 | 2.5323          | 0.5298   |
| 2.6753        | 248.32 | 184500 | 2.5286          | 0.5299   |
| 2.6679        | 248.99 | 185000 | 2.5276          | 0.5306   |
| 2.6679        | 249.66 | 185500 | 2.5249          | 0.5308   |
| 2.6679        | 250.34 | 186000 | 2.5308          | 0.5302   |
| 2.6679        | 251.01 | 186500 | 2.5307          | 0.5297   |
| 2.6679        | 251.68 | 187000 | 2.5293          | 0.5305   |
| 2.6679        | 252.36 | 187500 | 2.5255          | 0.5306   |
| 2.6679        | 253.03 | 188000 | 2.5244          | 0.5312   |
| 2.6679        | 253.7  | 188500 | 2.5278          | 0.5305   |
| 2.6679        | 254.37 | 189000 | 2.5212          | 0.5317   |
| 2.6679        | 255.05 | 189500 | 2.5256          | 0.5307   |
| 2.6611        | 255.72 | 190000 | 2.5273          | 0.5303   |
| 2.6611        | 256.39 | 190500 | 2.5222          | 0.5310   |
| 2.6611        | 257.07 | 191000 | 2.5237          | 0.5311   |
| 2.6611        | 257.74 | 191500 | 2.5258          | 0.5309   |
| 2.6611        | 258.41 | 192000 | 2.5219          | 0.5313   |
| 2.6611        | 259.08 | 192500 | 2.5243          | 0.5314   |
| 2.6611        | 259.76 | 193000 | 2.5203          | 0.5319   |
| 2.6611        | 260.43 | 193500 | 2.5205          | 0.5313   |
| 2.6611        | 261.1  | 194000 | 2.5205          | 0.5322   |
| 2.6611        | 261.78 | 194500 | 2.5196          | 0.5317   |
| 2.655         | 262.45 | 195000 | 2.5199          | 0.5315   |
| 2.655         | 263.12 | 195500 | 2.5226          | 0.5315   |
| 2.655         | 263.8  | 196000 | 2.5175          | 0.5316   |
| 2.655         | 264.47 | 196500 | 2.5160          | 0.5322   |
| 2.655         | 265.14 | 197000 | 2.5185          | 0.5316   |
| 2.655         | 265.81 | 197500 | 2.5133          | 0.5322   |
| 2.655         | 266.49 | 198000 | 2.5163          | 0.5318   |
| 2.655         | 267.16 | 198500 | 2.5135          | 0.5325   |
| 2.655         | 267.83 | 199000 | 2.5132          | 0.5326   |
| 2.655         | 268.51 | 199500 | 2.5148          | 0.5323   |
| 2.6486        | 269.18 | 200000 | 2.5194          | 0.5317   |
| 2.6486        | 269.85 | 200500 | 2.5162          | 0.5321   |
| 2.6486        | 270.52 | 201000 | 2.5090          | 0.5332   |
| 2.6486        | 271.2  | 201500 | 2.5126          | 0.5325   |
| 2.6486        | 271.87 | 202000 | 2.5155          | 0.5320   |
| 2.6486        | 272.54 | 202500 | 2.5099          | 0.5329   |
| 2.6486        | 273.22 | 203000 | 2.5130          | 0.5325   |
| 2.6486        | 273.89 | 203500 | 2.5064          | 0.5329   |
| 2.6486        | 274.56 | 204000 | 2.5154          | 0.5319   |
| 2.6486        | 275.24 | 204500 | 2.5097          | 0.5329   |
| 2.6433        | 275.91 | 205000 | 2.5075          | 0.5334   |
| 2.6433        | 276.58 | 205500 | 2.5120          | 0.5325   |
| 2.6433        | 277.25 | 206000 | 2.5100          | 0.5329   |
| 2.6433        | 277.93 | 206500 | 2.5115          | 0.5332   |
| 2.6433        | 278.6  | 207000 | 2.5071          | 0.5332   |
| 2.6433        | 279.27 | 207500 | 2.5075          | 0.5335   |
| 2.6433        | 279.95 | 208000 | 2.5020          | 0.5338   |
| 2.6433        | 280.62 | 208500 | 2.5025          | 0.5340   |
| 2.6433        | 281.29 | 209000 | 2.5064          | 0.5333   |
| 2.6433        | 281.96 | 209500 | 2.5038          | 0.5336   |
| 2.6383        | 282.64 | 210000 | 2.5041          | 0.5340   |
| 2.6383        | 283.31 | 210500 | 2.5075          | 0.5336   |
| 2.6383        | 283.98 | 211000 | 2.5028          | 0.5333   |
| 2.6383        | 284.66 | 211500 | 2.5008          | 0.5340   |
| 2.6383        | 285.33 | 212000 | 2.5005          | 0.5345   |
| 2.6383        | 286.0  | 212500 | 2.5020          | 0.5334   |
| 2.6383        | 286.68 | 213000 | 2.5011          | 0.5344   |
| 2.6383        | 287.35 | 213500 | 2.5028          | 0.5338   |
| 2.6383        | 288.02 | 214000 | 2.4970          | 0.5340   |
| 2.6383        | 288.69 | 214500 | 2.4995          | 0.5343   |
| 2.6336        | 289.37 | 215000 | 2.5010          | 0.5343   |
| 2.6336        | 290.04 | 215500 | 2.5060          | 0.5336   |
| 2.6336        | 290.71 | 216000 | 2.4955          | 0.5347   |
| 2.6336        | 291.39 | 216500 | 2.4972          | 0.5349   |
| 2.6336        | 292.06 | 217000 | 2.4977          | 0.5349   |
| 2.6336        | 292.73 | 217500 | 2.4973          | 0.5346   |
| 2.6336        | 293.4  | 218000 | 2.4981          | 0.5346   |
| 2.6336        | 294.08 | 218500 | 2.4941          | 0.5346   |
| 2.6336        | 294.75 | 219000 | 2.4978          | 0.5350   |
| 2.6336        | 295.42 | 219500 | 2.4990          | 0.5343   |
| 2.6288        | 296.1  | 220000 | 2.4929          | 0.5347   |
| 2.6288        | 296.77 | 220500 | 2.4937          | 0.5349   |
| 2.6288        | 297.44 | 221000 | 2.4938          | 0.5349   |
| 2.6288        | 298.12 | 221500 | 2.4938          | 0.5343   |
| 2.6288        | 298.79 | 222000 | 2.4924          | 0.5354   |
| 2.6288        | 299.46 | 222500 | 2.4953          | 0.5348   |
| 2.6288        | 300.13 | 223000 | 2.4930          | 0.5347   |
| 2.6288        | 300.81 | 223500 | 2.4934          | 0.5353   |
| 2.6288        | 301.48 | 224000 | 2.4942          | 0.5348   |
| 2.6288        | 302.15 | 224500 | 2.4960          | 0.5344   |
| 2.6246        | 302.83 | 225000 | 2.4875          | 0.5357   |
| 2.6246        | 303.5  | 225500 | 2.4898          | 0.5355   |
| 2.6246        | 304.17 | 226000 | 2.4847          | 0.5366   |
| 2.6246        | 304.84 | 226500 | 2.4970          | 0.5348   |
| 2.6246        | 305.52 | 227000 | 2.4905          | 0.5356   |
| 2.6246        | 306.19 | 227500 | 2.4873          | 0.5361   |
| 2.6246        | 306.86 | 228000 | 2.4939          | 0.5350   |
| 2.6246        | 307.54 | 228500 | 2.4910          | 0.5360   |
| 2.6246        | 308.21 | 229000 | 2.4886          | 0.5355   |
| 2.6246        | 308.88 | 229500 | 2.4890          | 0.5369   |
| 2.6207        | 309.56 | 230000 | 2.4900          | 0.5360   |
| 2.6207        | 310.23 | 230500 | 2.4885          | 0.5354   |
| 2.6207        | 310.9  | 231000 | 2.4895          | 0.5358   |
| 2.6207        | 311.57 | 231500 | 2.4871          | 0.5358   |
| 2.6207        | 312.25 | 232000 | 2.4914          | 0.5352   |
| 2.6207        | 312.92 | 232500 | 2.4843          | 0.5366   |
| 2.6207        | 313.59 | 233000 | 2.4837          | 0.5365   |
| 2.6207        | 314.27 | 233500 | 2.4883          | 0.5360   |
| 2.6207        | 314.94 | 234000 | 2.4839          | 0.5366   |
| 2.6207        | 315.61 | 234500 | 2.4854          | 0.5366   |
| 2.6171        | 316.29 | 235000 | 2.4833          | 0.5367   |
| 2.6171        | 316.96 | 235500 | 2.4783          | 0.5374   |
| 2.6171        | 317.63 | 236000 | 2.4807          | 0.5370   |
| 2.6171        | 318.3  | 236500 | 2.4824          | 0.5366   |
| 2.6171        | 318.98 | 237000 | 2.4857          | 0.5361   |
| 2.6171        | 319.65 | 237500 | 2.4817          | 0.5366   |
| 2.6171        | 320.32 | 238000 | 2.4855          | 0.5364   |
| 2.6171        | 321.0  | 238500 | 2.4834          | 0.5367   |
| 2.6171        | 321.67 | 239000 | 2.4831          | 0.5363   |
| 2.6171        | 322.34 | 239500 | 2.4806          | 0.5370   |
| 2.6134        | 323.01 | 240000 | 2.4842          | 0.5365   |
| 2.6134        | 323.69 | 240500 | 2.4830          | 0.5364   |
| 2.6134        | 324.36 | 241000 | 2.4822          | 0.5367   |
| 2.6134        | 325.03 | 241500 | 2.4805          | 0.5373   |
| 2.6134        | 325.71 | 242000 | 2.4838          | 0.5365   |
| 2.6134        | 326.38 | 242500 | 2.4776          | 0.5371   |
| 2.6134        | 327.05 | 243000 | 2.4786          | 0.5376   |
| 2.6134        | 327.73 | 243500 | 2.4824          | 0.5371   |
| 2.6134        | 328.4  | 244000 | 2.4842          | 0.5363   |
| 2.6134        | 329.07 | 244500 | 2.4790          | 0.5375   |
| 2.6107        | 329.74 | 245000 | 2.4770          | 0.5372   |
| 2.6107        | 330.42 | 245500 | 2.4805          | 0.5375   |
| 2.6107        | 331.09 | 246000 | 2.4839          | 0.5370   |
| 2.6107        | 331.76 | 246500 | 2.4802          | 0.5367   |
| 2.6107        | 332.44 | 247000 | 2.4796          | 0.5373   |
| 2.6107        | 333.11 | 247500 | 2.4736          | 0.5377   |
| 2.6107        | 333.78 | 248000 | 2.4789          | 0.5374   |
| 2.6107        | 334.45 | 248500 | 2.4761          | 0.5375   |
| 2.6107        | 335.13 | 249000 | 2.4728          | 0.5379   |
| 2.6107        | 335.8  | 249500 | 2.4702          | 0.5386   |
| 2.608         | 336.47 | 250000 | 2.4764          | 0.5377   |
| 2.608         | 337.15 | 250500 | 2.4738          | 0.5380   |
| 2.608         | 337.82 | 251000 | 2.4795          | 0.5371   |
| 2.608         | 338.49 | 251500 | 2.4702          | 0.5387   |
| 2.608         | 339.17 | 252000 | 2.4823          | 0.5369   |
| 2.608         | 339.84 | 252500 | 2.4741          | 0.5382   |
| 2.608         | 340.51 | 253000 | 2.4718          | 0.5382   |
| 2.608         | 341.18 | 253500 | 2.4731          | 0.5378   |
| 2.608         | 341.86 | 254000 | 2.4780          | 0.5373   |
| 2.608         | 342.53 | 254500 | 2.4706          | 0.5388   |
| 2.6058        | 343.2  | 255000 | 2.4707          | 0.5386   |
| 2.6058        | 343.88 | 255500 | 2.4725          | 0.5380   |
| 2.6058        | 344.55 | 256000 | 2.4744          | 0.5382   |
| 2.6058        | 345.22 | 256500 | 2.4766          | 0.5374   |
| 2.6058        | 345.89 | 257000 | 2.4736          | 0.5378   |
| 2.6058        | 346.57 | 257500 | 2.4731          | 0.5383   |
| 2.6058        | 347.24 | 258000 | 2.4754          | 0.5377   |
| 2.6058        | 347.91 | 258500 | 2.4749          | 0.5382   |
| 2.6058        | 348.59 | 259000 | 2.4735          | 0.5378   |
| 2.6058        | 349.26 | 259500 | 2.4716          | 0.5384   |
| 2.6027        | 349.93 | 260000 | 2.4726          | 0.5378   |
| 2.6027        | 350.61 | 260500 | 2.4733          | 0.5378   |
| 2.6027        | 351.28 | 261000 | 2.4698          | 0.5386   |
| 2.6027        | 351.95 | 261500 | 2.4702          | 0.5388   |
| 2.6027        | 352.62 | 262000 | 2.4673          | 0.5390   |
| 2.6027        | 353.3  | 262500 | 2.4683          | 0.5390   |
| 2.6027        | 353.97 | 263000 | 2.4739          | 0.5379   |
| 2.6027        | 354.64 | 263500 | 2.4743          | 0.5382   |
| 2.6027        | 355.32 | 264000 | 2.4694          | 0.5388   |
| 2.6027        | 355.99 | 264500 | 2.4671          | 0.5391   |
| 2.6009        | 356.66 | 265000 | 2.4747          | 0.5383   |
| 2.6009        | 357.34 | 265500 | 2.4703          | 0.5382   |
| 2.6009        | 358.01 | 266000 | 2.4695          | 0.5388   |
| 2.6009        | 358.68 | 266500 | 2.4725          | 0.5380   |
| 2.6009        | 359.35 | 267000 | 2.4639          | 0.5397   |
| 2.6009        | 360.03 | 267500 | 2.4686          | 0.5385   |
| 2.6009        | 360.7  | 268000 | 2.4698          | 0.5386   |
| 2.6009        | 361.37 | 268500 | 2.4694          | 0.5386   |
| 2.6009        | 362.05 | 269000 | 2.4680          | 0.5390   |
| 2.6009        | 362.72 | 269500 | 2.4728          | 0.5383   |
| 2.5989        | 363.39 | 270000 | 2.4697          | 0.5385   |
| 2.5989        | 364.06 | 270500 | 2.4701          | 0.5387   |
| 2.5989        | 364.74 | 271000 | 2.4702          | 0.5387   |
| 2.5989        | 365.41 | 271500 | 2.4687          | 0.5390   |
| 2.5989        | 366.08 | 272000 | 2.4725          | 0.5382   |
| 2.5989        | 366.76 | 272500 | 2.4673          | 0.5384   |
| 2.5989        | 367.43 | 273000 | 2.4659          | 0.5390   |
| 2.5989        | 368.1  | 273500 | 2.4686          | 0.5389   |
| 2.5989        | 368.78 | 274000 | 2.4677          | 0.5382   |
| 2.5989        | 369.45 | 274500 | 2.4632          | 0.5389   |
| 2.5977        | 370.12 | 275000 | 2.4676          | 0.5385   |
| 2.5977        | 370.79 | 275500 | 2.4699          | 0.5388   |
| 2.5977        | 371.47 | 276000 | 2.4629          | 0.5394   |
| 2.5977        | 372.14 | 276500 | 2.4720          | 0.5380   |
| 2.5977        | 372.81 | 277000 | 2.4678          | 0.5391   |
| 2.5977        | 373.49 | 277500 | 2.4643          | 0.5396   |
| 2.5977        | 374.16 | 278000 | 2.4654          | 0.5395   |
| 2.5977        | 374.83 | 278500 | 2.4645          | 0.5395   |
| 2.5977        | 375.5  | 279000 | 2.4649          | 0.5391   |
| 2.5977        | 376.18 | 279500 | 2.4639          | 0.5392   |
| 2.5961        | 376.85 | 280000 | 2.4659          | 0.5389   |
| 2.5961        | 377.52 | 280500 | 2.4681          | 0.5385   |
| 2.5961        | 378.2  | 281000 | 2.4641          | 0.5390   |
| 2.5961        | 378.87 | 281500 | 2.4658          | 0.5393   |
| 2.5961        | 379.54 | 282000 | 2.4687          | 0.5388   |
| 2.5961        | 380.22 | 282500 | 2.4690          | 0.5385   |
| 2.5961        | 380.89 | 283000 | 2.4679          | 0.5391   |
| 2.5961        | 381.56 | 283500 | 2.4612          | 0.5395   |
| 2.5961        | 382.23 | 284000 | 2.4624          | 0.5395   |
| 2.5961        | 382.91 | 284500 | 2.4668          | 0.5390   |
| 2.5947        | 383.58 | 285000 | 2.4663          | 0.5389   |
| 2.5947        | 384.25 | 285500 | 2.4654          | 0.5387   |
| 2.5947        | 384.93 | 286000 | 2.4708          | 0.5385   |
| 2.5947        | 385.6  | 286500 | 2.4669          | 0.5388   |
| 2.5947        | 386.27 | 287000 | 2.4612          | 0.5396   |
| 2.5947        | 386.94 | 287500 | 2.4666          | 0.5392   |
| 2.5947        | 387.62 | 288000 | 2.4653          | 0.5393   |
| 2.5947        | 388.29 | 288500 | 2.4666          | 0.5390   |
| 2.5947        | 388.96 | 289000 | 2.4684          | 0.5388   |
| 2.5947        | 389.64 | 289500 | 2.4660          | 0.5394   |
| 2.5936        | 390.31 | 290000 | 2.4642          | 0.5395   |
| 2.5936        | 390.98 | 290500 | 2.4627          | 0.5403   |
| 2.5936        | 391.66 | 291000 | 2.4683          | 0.5389   |
| 2.5936        | 392.33 | 291500 | 2.4667          | 0.5387   |
| 2.5936        | 393.0  | 292000 | 2.4660          | 0.5389   |
| 2.5936        | 393.67 | 292500 | 2.4673          | 0.5390   |
| 2.5936        | 394.35 | 293000 | 2.4645          | 0.5391   |
| 2.5936        | 395.02 | 293500 | 2.4693          | 0.5389   |
| 2.5936        | 395.69 | 294000 | 2.4692          | 0.5385   |
| 2.5936        | 396.37 | 294500 | 2.4653          | 0.5385   |
| 2.5934        | 397.04 | 295000 | 2.4661          | 0.5390   |
| 2.5934        | 397.71 | 295500 | 2.4630          | 0.5394   |
| 2.5934        | 398.38 | 296000 | 2.4641          | 0.5390   |
| 2.5934        | 399.06 | 296500 | 2.4636          | 0.5392   |
| 2.5934        | 399.73 | 297000 | 2.4650          | 0.5392   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1

### Additional configurations

```
data:
  dataset_name: cc100
  lang: nl
  overwrite_cache: False
  validation_split_percentage: 5
  max_seq_length: 512
  preprocessing_num_workers: 8
  mlm_probability: 0.15
  line_by_line: False
  pad_to_max_length: False
  max_train_samples: -1
  max_eval_samples: -1

training:
  do_train: True
  do_eval: True
  do_predict: True
  resume_from_checkpoint: False
  evaluation_strategy: steps
  eval_steps: 500
  per_device_train_batch_size: 16
  per_device_eval_batch_size: 16
  gradient_accumulation_steps: 32
  eval_accumulation_steps: 1
  learning_rate: 5e-5
  weight_decay: 0.0
  adam_beta1: 0.9
  adam_beta2: 0.999
  adam_epsilon: 1e-8
  max_grad_norm: 1.0
  num_train_epochs: 400.0
  lr_scheduler_type: linear
  fp16: False
  warmup_steps: 8000
  seed: 703
```
{"tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "nl_electra", "results": []}]}
transformers pytorch electra fill-mask generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #electra #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

nl\_electra
===========


This model is a pretrained version of ELECTRA on the Dutch subset of the CC100 dataset.
It achieves the following results on the evaluation set:


* Loss: 2.4650
* Accuracy: 0.5392


Training procedure
------------------


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 703
* gradient\_accumulation\_steps: 32
* total\_train\_batch\_size: 512
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 8000
* num\_epochs: 400.0


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu102
* Datasets 2.3.2
* Tokenizers 0.12.1


### Additional configurations



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 703
* gradient\_accumulation\_steps: 32
* total\_train\_batch\_size: 512
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 8000
* num\_epochs: 400.0 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu102
* Datasets 2.3.2
* Tokenizers 0.12.1 ### Additional configurations
TAGS
#transformers #pytorch #electra #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 703
* gradient\_accumulation\_steps: 32
* total\_train\_batch\_size: 512
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 8000
* num\_epochs: 400.0 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu102
* Datasets 2.3.2
* Tokenizers 0.12.1 ### Additional configurations
passage: TAGS
#transformers #pytorch #electra #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 703
* gradient\_accumulation\_steps: 32
* total\_train\_batch\_size: 512
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 8000
* num\_epochs: 400.0### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu102
* Datasets 2.3.2
* Tokenizers 0.12.1### Additional configurations