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# roberta-finetuned-token-reqadjinsiders

This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-bne](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0597
- F1 B-cadj: 0
- F1 I-cadj: 0.4734
- F1 B-peso: 0
- F1 I-peso: 0
- Macro F1: 0.1183

## 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: 0.0002
- 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 | F1 B-cadj | F1 I-cadj | F1 B-peso | F1 I-peso | Macro F1 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:---------:|:---------:|:---------:|:--------:|
| 0.2188        | 1.0   | 10   | 0.0758          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0711        | 2.0   | 20   | 0.0678          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0656        | 3.0   | 30   | 0.0639          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0634        | 4.0   | 40   | 0.0629          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0624        | 5.0   | 50   | 0.0615          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0602        | 6.0   | 60   | 0.0598          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0573        | 7.0   | 70   | 0.0628          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0537        | 8.0   | 80   | 0.0531          | 0         | 0.1373    | 0         | 0         | 0.0343   |
| 0.0595        | 9.0   | 90   | 0.0565          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0435        | 10.0  | 100  | 0.0659          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0507        | 11.0  | 110  | 0.0558          | 0         | 0.4549    | 0         | 0         | 0.1137   |
| 0.0313        | 12.0  | 120  | 0.0561          | 0         | 0.3955    | 0         | 0         | 0.0989   |
| 0.0278        | 13.0  | 130  | 0.0629          | 0         | 0.3756    | 0         | 0         | 0.0939   |
| 0.0248        | 14.0  | 140  | 0.0634          | 0         | 0.3726    | 0         | 0         | 0.0932   |
| 0.0282        | 15.0  | 150  | 0.0607          | 0         | 0.3303    | 0         | 0         | 0.0826   |
| 0.0302        | 16.0  | 160  | 0.0628          | 0         | 0.4428    | 0         | 0         | 0.1107   |
| 0.0205        | 17.0  | 170  | 0.0551          | 0         | 0.3855    | 0         | 0         | 0.0964   |
| 0.0186        | 18.0  | 180  | 0.0627          | 0         | 0.4419    | 0         | 0         | 0.1105   |
| 0.0171        | 19.0  | 190  | 0.0721          | 0         | 0.3524    | 0         | 0         | 0.0881   |
| 0.0152        | 20.0  | 200  | 0.0574          | 0         | 0.3281    | 0         | 0         | 0.0820   |
| 0.0152        | 21.0  | 210  | 0.0597          | 0         | 0.1515    | 0         | 0         | 0.0379   |
| 0.0157        | 22.0  | 220  | 0.0675          | 0         | 0.3633    | 0         | 0         | 0.0908   |
| 0.0135        | 23.0  | 230  | 0.0728          | 0         | 0.3135    | 0         | 0         | 0.0784   |
| 0.0128        | 24.0  | 240  | 0.0703          | 0         | 0.4114    | 0         | 0         | 0.1028   |
| 0.0126        | 25.0  | 250  | 0.0605          | 0         | 0.3695    | 0         | 0         | 0.0924   |
| 0.0228        | 26.0  | 260  | 0.0490          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0266        | 27.0  | 270  | 0.0819          | 0         | 0.2214    | 0         | 0         | 0.0554   |
| 0.0512        | 28.0  | 280  | 0.0598          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0625        | 29.0  | 290  | 0.0595          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0601        | 30.0  | 300  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0595        | 31.0  | 310  | 0.0594          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0597        | 32.0  | 320  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 33.0  | 330  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0599        | 34.0  | 340  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0601        | 35.0  | 350  | 0.0599          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0597        | 36.0  | 360  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0595        | 37.0  | 370  | 0.0594          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0595        | 38.0  | 380  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 39.0  | 390  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 40.0  | 400  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0595        | 41.0  | 410  | 0.0594          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 42.0  | 420  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 43.0  | 430  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 44.0  | 440  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 45.0  | 450  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 46.0  | 460  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 47.0  | 470  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 48.0  | 480  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0596        | 49.0  | 490  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 50.0  | 500  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0595        | 51.0  | 510  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 52.0  | 520  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 53.0  | 530  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0597        | 54.0  | 540  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 55.0  | 550  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0601        | 56.0  | 560  | 0.0594          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0595        | 57.0  | 570  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0595        | 58.0  | 580  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 59.0  | 590  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 60.0  | 600  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 61.0  | 610  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 62.0  | 620  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 63.0  | 630  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0595        | 64.0  | 640  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 65.0  | 650  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0581        | 66.0  | 660  | 0.0580          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0503        | 67.0  | 670  | 0.0608          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0338        | 68.0  | 680  | 0.0653          | 0         | 0.2763    | 0         | 0         | 0.0691   |
| 0.0311        | 69.0  | 690  | 0.0727          | 0         | 0.3019    | 0         | 0         | 0.0755   |
| 0.0305        | 70.0  | 700  | 0.0683          | 0         | 0.3515    | 0         | 0         | 0.0879   |
| 0.0236        | 71.0  | 710  | 0.0757          | 0         | 0.2626    | 0         | 0         | 0.0656   |
| 0.0261        | 72.0  | 720  | 0.0597          | 0         | 0.4734    | 0         | 0         | 0.1183   |
| 0.0242        | 73.0  | 730  | 0.0621          | 0         | 0.4411    | 0         | 0         | 0.1103   |
| 0.0293        | 74.0  | 740  | 0.0722          | 0         | 0.3305    | 0         | 0         | 0.0826   |
| 0.0465        | 75.0  | 750  | 0.0600          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0598        | 76.0  | 760  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 77.0  | 770  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 78.0  | 780  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0602        | 79.0  | 790  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0598        | 80.0  | 800  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0595        | 81.0  | 810  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 82.0  | 820  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 83.0  | 830  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 84.0  | 840  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 85.0  | 850  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 86.0  | 860  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0597        | 87.0  | 870  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 88.0  | 880  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.06          | 89.0  | 890  | 0.0595          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 90.0  | 900  | 0.0594          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 91.0  | 910  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 92.0  | 920  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 93.0  | 930  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 94.0  | 940  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 95.0  | 950  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 96.0  | 960  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 97.0  | 970  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0596        | 98.0  | 980  | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 99.0  | 990  | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 100.0 | 1000 | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0596        | 101.0 | 1010 | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 102.0 | 1020 | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 103.0 | 1030 | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 104.0 | 1040 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.059         | 105.0 | 1050 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 106.0 | 1060 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0595        | 107.0 | 1070 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0599        | 108.0 | 1080 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0598        | 109.0 | 1090 | 0.0594          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0595        | 110.0 | 1100 | 0.0594          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 111.0 | 1110 | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0596        | 112.0 | 1120 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 113.0 | 1130 | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 114.0 | 1140 | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 115.0 | 1150 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.059         | 116.0 | 1160 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 117.0 | 1170 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 118.0 | 1180 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 119.0 | 1190 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 120.0 | 1200 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 121.0 | 1210 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 122.0 | 1220 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 123.0 | 1230 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 124.0 | 1240 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 125.0 | 1250 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.059         | 126.0 | 1260 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 127.0 | 1270 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0595        | 128.0 | 1280 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 129.0 | 1290 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.059         | 130.0 | 1300 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.059         | 131.0 | 1310 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 132.0 | 1320 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 133.0 | 1330 | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 134.0 | 1340 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0596        | 135.0 | 1350 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 136.0 | 1360 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0596        | 137.0 | 1370 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 138.0 | 1380 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 139.0 | 1390 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0595        | 140.0 | 1400 | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 141.0 | 1410 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 142.0 | 1420 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 143.0 | 1430 | 0.0593          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 144.0 | 1440 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.059         | 145.0 | 1450 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.059         | 146.0 | 1460 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.059         | 147.0 | 1470 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 148.0 | 1480 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 149.0 | 1490 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 150.0 | 1500 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 151.0 | 1510 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 152.0 | 1520 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 153.0 | 1530 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 154.0 | 1540 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.059         | 155.0 | 1550 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 156.0 | 1560 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 157.0 | 1570 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0597        | 158.0 | 1580 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 159.0 | 1590 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 160.0 | 1600 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0597        | 161.0 | 1610 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 162.0 | 1620 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0594        | 163.0 | 1630 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0595        | 164.0 | 1640 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0597        | 165.0 | 1650 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 166.0 | 1660 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 167.0 | 1670 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 168.0 | 1680 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0597        | 169.0 | 1690 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 170.0 | 1700 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.059         | 171.0 | 1710 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 172.0 | 1720 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 173.0 | 1730 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.059         | 174.0 | 1740 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 175.0 | 1750 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0589        | 176.0 | 1760 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 177.0 | 1770 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 178.0 | 1780 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 179.0 | 1790 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 180.0 | 1800 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.059         | 181.0 | 1810 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 182.0 | 1820 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.059         | 183.0 | 1830 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 184.0 | 1840 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 185.0 | 1850 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 186.0 | 1860 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 187.0 | 1870 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0598        | 188.0 | 1880 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 189.0 | 1890 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0591        | 190.0 | 1900 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 191.0 | 1910 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0599        | 192.0 | 1920 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 193.0 | 1930 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0595        | 194.0 | 1940 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0593        | 195.0 | 1950 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 196.0 | 1960 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.059         | 197.0 | 1970 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0589        | 198.0 | 1980 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0592        | 199.0 | 1990 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |
| 0.0589        | 200.0 | 2000 | 0.0592          | 0         | 0         | 0         | 0         | 0.0      |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "roberta-finetuned-token-reqadjinsiders", "results": []}]}
transformers pytorch tensorboard roberta generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

roberta-finetuned-token-reqadjinsiders
======================================


This model is a fine-tuned version of PlanTL-GOB-ES/roberta-base-bne on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0597
* F1 B-cadj: 0
* F1 I-cadj: 0.4734
* F1 B-peso: 0
* F1 I-peso: 0
* Macro F1: 0.1183


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: 0.0002
* 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 4.30.0.dev0
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* 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 4.30.0.dev0
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #roberta #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0002
* 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 4.30.0.dev0
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3