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# longformer-base-4096-bne-es-finetuned-augmented1

This model is a fine-tuned version of [PlanTL-GOB-ES/longformer-base-4096-bne-es](https://huggingface.co/PlanTL-GOB-ES/longformer-base-4096-bne-es) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7936
- Precision: 0.5307
- Recall: 0.6189
- F1: 0.5714
- Accuracy: 0.8447

## 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: 4
- eval_batch_size: 4
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.723         | 1.0   | 713   | 0.5777          | 0.3428    | 0.5358 | 0.4181 | 0.8332   |
| 0.3414        | 2.0   | 1426  | 0.7079          | 0.3337    | 0.5462 | 0.4143 | 0.8210   |
| 0.1307        | 3.0   | 2139  | 0.7862          | 0.4226    | 0.5868 | 0.4913 | 0.8298   |
| 0.0792        | 4.0   | 2852  | 0.9581          | 0.4215    | 0.5906 | 0.4919 | 0.8245   |
| 0.0427        | 5.0   | 3565  | 1.0090          | 0.4451    | 0.6047 | 0.5128 | 0.8303   |
| 0.032         | 6.0   | 4278  | 1.0855          | 0.4865    | 0.6123 | 0.5422 | 0.8450   |
| 0.0237        | 7.0   | 4991  | 1.1150          | 0.4693    | 0.6066 | 0.5292 | 0.8455   |
| 0.0171        | 8.0   | 5704  | 1.1544          | 0.4778    | 0.5991 | 0.5316 | 0.8456   |
| 0.0155        | 9.0   | 6417  | 1.1691          | 0.4812    | 0.6038 | 0.5356 | 0.8421   |
| 0.0114        | 10.0  | 7130  | 1.2833          | 0.4861    | 0.6104 | 0.5412 | 0.8349   |
| 0.0137        | 11.0  | 7843  | 1.2716          | 0.4594    | 0.6028 | 0.5214 | 0.8334   |
| 0.0104        | 12.0  | 8556  | 1.2635          | 0.4571    | 0.5981 | 0.5182 | 0.8459   |
| 0.0053        | 13.0  | 9269  | 1.2427          | 0.4447    | 0.6066 | 0.5132 | 0.8419   |
| 0.0067        | 14.0  | 9982  | 1.2834          | 0.4862    | 0.6    | 0.5372 | 0.8432   |
| 0.0068        | 15.0  | 10695 | 1.3774          | 0.5012    | 0.6094 | 0.5500 | 0.8373   |
| 0.0077        | 16.0  | 11408 | 1.3625          | 0.4871    | 0.6057 | 0.5399 | 0.8428   |
| 0.0051        | 17.0  | 12121 | 1.3764          | 0.5       | 0.6113 | 0.5501 | 0.8445   |
| 0.0061        | 18.0  | 12834 | 1.5528          | 0.4613    | 0.6009 | 0.5219 | 0.8267   |
| 0.0049        | 19.0  | 13547 | 1.3307          | 0.5070    | 0.6151 | 0.5558 | 0.8538   |
| 0.0059        | 20.0  | 14260 | 1.3556          | 0.4903    | 0.6198 | 0.5475 | 0.8439   |
| 0.0064        | 21.0  | 14973 | 1.4599          | 0.5004    | 0.6123 | 0.5507 | 0.8409   |
| 0.0057        | 22.0  | 15686 | 1.3506          | 0.5077    | 0.6217 | 0.5589 | 0.8439   |
| 0.0054        | 23.0  | 16399 | 1.5439          | 0.4914    | 0.5953 | 0.5384 | 0.8377   |
| 0.0034        | 24.0  | 17112 | 1.5174          | 0.5059    | 0.6066 | 0.5517 | 0.8377   |
| 0.0048        | 25.0  | 17825 | 1.5228          | 0.4984    | 0.6057 | 0.5468 | 0.8438   |
| 0.0041        | 26.0  | 18538 | 1.4479          | 0.5224    | 0.6057 | 0.5609 | 0.8403   |
| 0.0049        | 27.0  | 19251 | 1.3992          | 0.5291    | 0.6349 | 0.5772 | 0.8447   |
| 0.0048        | 28.0  | 19964 | 1.4971          | 0.5234    | 0.6321 | 0.5726 | 0.8478   |
| 0.0018        | 29.0  | 20677 | 1.4874          | 0.4981    | 0.6151 | 0.5504 | 0.8390   |
| 0.0035        | 30.0  | 21390 | 1.3051          | 0.5051    | 0.6094 | 0.5524 | 0.8421   |
| 0.0031        | 31.0  | 22103 | 1.5998          | 0.5133    | 0.6179 | 0.5608 | 0.8364   |
| 0.0031        | 32.0  | 22816 | 1.4274          | 0.5085    | 0.6179 | 0.5579 | 0.8458   |
| 0.0042        | 33.0  | 23529 | 1.3180          | 0.5111    | 0.6066 | 0.5548 | 0.8494   |
| 0.0022        | 34.0  | 24242 | 1.5043          | 0.4886    | 0.6085 | 0.5420 | 0.8442   |
| 0.0021        | 35.0  | 24955 | 1.5247          | 0.4962    | 0.6094 | 0.5470 | 0.8425   |
| 0.0024        | 36.0  | 25668 | 1.5139          | 0.4851    | 0.5981 | 0.5357 | 0.8432   |
| 0.0027        | 37.0  | 26381 | 1.5214          | 0.4930    | 0.6009 | 0.5417 | 0.8404   |
| 0.0024        | 38.0  | 27094 | 1.4470          | 0.5087    | 0.6075 | 0.5537 | 0.8472   |
| 0.0009        | 39.0  | 27807 | 1.4867          | 0.5016    | 0.6094 | 0.5503 | 0.8485   |
| 0.0015        | 40.0  | 28520 | 1.5234          | 0.5148    | 0.6217 | 0.5632 | 0.8483   |
| 0.0023        | 41.0  | 29233 | 1.5742          | 0.4926    | 0.6264 | 0.5515 | 0.8407   |
| 0.0017        | 42.0  | 29946 | 1.5897          | 0.5252    | 0.6    | 0.5601 | 0.8403   |
| 0.0022        | 43.0  | 30659 | 1.4243          | 0.4889    | 0.6038 | 0.5403 | 0.8448   |
| 0.001         | 44.0  | 31372 | 1.6117          | 0.5081    | 0.6179 | 0.5577 | 0.8462   |
| 0.0015        | 45.0  | 32085 | 1.5342          | 0.5169    | 0.6066 | 0.5582 | 0.8405   |
| 0.0005        | 46.0  | 32798 | 1.5110          | 0.4687    | 0.6142 | 0.5316 | 0.8432   |
| 0.0019        | 47.0  | 33511 | 1.5835          | 0.5066    | 0.6132 | 0.5548 | 0.8427   |
| 0.0063        | 48.0  | 34224 | 1.5688          | 0.5058    | 0.5802 | 0.5404 | 0.8394   |
| 0.0017        | 49.0  | 34937 | 1.5410          | 0.5075    | 0.6028 | 0.5511 | 0.8419   |
| 0.0012        | 50.0  | 35650 | 1.5343          | 0.5220    | 0.5943 | 0.5558 | 0.8359   |
| 0.0009        | 51.0  | 36363 | 1.5190          | 0.5173    | 0.6358 | 0.5705 | 0.8411   |
| 0.0006        | 52.0  | 37076 | 1.6576          | 0.5066    | 0.6189 | 0.5571 | 0.8311   |
| 0.0009        | 53.0  | 37789 | 1.5675          | 0.5155    | 0.6283 | 0.5663 | 0.8475   |
| 0.0007        | 54.0  | 38502 | 1.6993          | 0.5218    | 0.6208 | 0.5670 | 0.8328   |
| 0.0019        | 55.0  | 39215 | 1.6003          | 0.5284    | 0.6047 | 0.5640 | 0.8365   |
| 0.0014        | 56.0  | 39928 | 1.4922          | 0.5428    | 0.6226 | 0.5800 | 0.8556   |
| 0.0004        | 57.0  | 40641 | 1.5974          | 0.5402    | 0.6142 | 0.5748 | 0.8464   |
| 0.0002        | 58.0  | 41354 | 1.7351          | 0.5501    | 0.6113 | 0.5791 | 0.8417   |
| 0.0008        | 59.0  | 42067 | 1.6191          | 0.5179    | 0.6132 | 0.5616 | 0.8476   |
| 0.0006        | 60.0  | 42780 | 1.5721          | 0.5059    | 0.6094 | 0.5528 | 0.8455   |
| 0.0009        | 61.0  | 43493 | 1.6079          | 0.4980    | 0.6    | 0.5443 | 0.8388   |
| 0.0011        | 62.0  | 44206 | 1.7208          | 0.4907    | 0.5943 | 0.5375 | 0.8288   |
| 0.0002        | 63.0  | 44919 | 1.7335          | 0.5012    | 0.5925 | 0.5430 | 0.8354   |
| 0.001         | 64.0  | 45632 | 1.7670          | 0.5439    | 0.6189 | 0.5790 | 0.8352   |
| 0.0002        | 65.0  | 46345 | 1.7687          | 0.5203    | 0.6170 | 0.5645 | 0.8430   |
| 0.0002        | 66.0  | 47058 | 1.7857          | 0.5059    | 0.6066 | 0.5517 | 0.8375   |
| 0.0003        | 67.0  | 47771 | 1.7961          | 0.5090    | 0.6104 | 0.5551 | 0.8335   |
| 0.0009        | 68.0  | 48484 | 1.7072          | 0.5039    | 0.6132 | 0.5532 | 0.8416   |
| 0.0003        | 69.0  | 49197 | 1.7345          | 0.5147    | 0.6113 | 0.5589 | 0.8421   |
| 0.0002        | 70.0  | 49910 | 1.6423          | 0.5427    | 0.6179 | 0.5779 | 0.8491   |
| 0.0007        | 71.0  | 50623 | 1.6966          | 0.5422    | 0.6368 | 0.5857 | 0.8425   |
| 0.0016        | 72.0  | 51336 | 1.7376          | 0.5153    | 0.6198 | 0.5627 | 0.8349   |
| 0.001         | 73.0  | 52049 | 1.6447          | 0.51      | 0.6255 | 0.5619 | 0.8442   |
| 0.0001        | 74.0  | 52762 | 1.7449          | 0.5204    | 0.6132 | 0.5630 | 0.8421   |
| 0.0002        | 75.0  | 53475 | 1.6948          | 0.5287    | 0.6179 | 0.5698 | 0.8450   |
| 0.0005        | 76.0  | 54188 | 1.6546          | 0.5305    | 0.6321 | 0.5768 | 0.8480   |
| 0.0002        | 77.0  | 54901 | 1.7188          | 0.5224    | 0.6264 | 0.5697 | 0.8444   |
| 0.0001        | 78.0  | 55614 | 1.6167          | 0.5102    | 0.6142 | 0.5574 | 0.8462   |
| 0.0005        | 79.0  | 56327 | 1.6709          | 0.5160    | 0.6245 | 0.5651 | 0.8462   |
| 0.0           | 80.0  | 57040 | 1.6883          | 0.5223    | 0.6179 | 0.5661 | 0.8475   |
| 0.0002        | 81.0  | 57753 | 1.7612          | 0.5051    | 0.6057 | 0.5508 | 0.8436   |
| 0.0001        | 82.0  | 58466 | 1.7766          | 0.5342    | 0.6189 | 0.5734 | 0.8410   |
| 0.0001        | 83.0  | 59179 | 1.7235          | 0.5252    | 0.6189 | 0.5682 | 0.8453   |
| 0.0002        | 84.0  | 59892 | 1.7663          | 0.5319    | 0.6208 | 0.5729 | 0.8440   |
| 0.0007        | 85.0  | 60605 | 1.7581          | 0.5280    | 0.6217 | 0.5711 | 0.8408   |
| 0.0002        | 86.0  | 61318 | 1.7467          | 0.5271    | 0.6236 | 0.5713 | 0.8407   |
| 0.0003        | 87.0  | 62031 | 1.7220          | 0.5275    | 0.6151 | 0.5679 | 0.8437   |
| 0.0001        | 88.0  | 62744 | 1.7616          | 0.5207    | 0.6179 | 0.5651 | 0.8430   |
| 0.0           | 89.0  | 63457 | 1.7817          | 0.5396    | 0.6170 | 0.5757 | 0.8460   |
| 0.0           | 90.0  | 64170 | 1.7684          | 0.5319    | 0.6132 | 0.5697 | 0.8436   |
| 0.0           | 91.0  | 64883 | 1.7731          | 0.5264    | 0.6208 | 0.5697 | 0.8434   |
| 0.0           | 92.0  | 65596 | 1.7448          | 0.5314    | 0.6236 | 0.5738 | 0.8467   |
| 0.0           | 93.0  | 66309 | 1.7457          | 0.5353    | 0.6302 | 0.5789 | 0.8484   |
| 0.0           | 94.0  | 67022 | 1.7477          | 0.5424    | 0.6274 | 0.5818 | 0.8485   |
| 0.0           | 95.0  | 67735 | 1.7931          | 0.5292    | 0.6160 | 0.5693 | 0.8444   |
| 0.0002        | 96.0  | 68448 | 1.8056          | 0.5287    | 0.6170 | 0.5694 | 0.8455   |
| 0.0001        | 97.0  | 69161 | 1.7963          | 0.5247    | 0.6217 | 0.5691 | 0.8450   |
| 0.0001        | 98.0  | 69874 | 1.7963          | 0.5211    | 0.6179 | 0.5654 | 0.8446   |
| 0.0001        | 99.0  | 70587 | 1.7950          | 0.5261    | 0.6189 | 0.5687 | 0.8452   |
| 0.0002        | 100.0 | 71300 | 1.7936          | 0.5307    | 0.6189 | 0.5714 | 0.8447   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "longformer-base-4096-bne-es-finetuned-augmented1", "results": []}]}
transformers pytorch longformer token-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #longformer #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

longformer-base-4096-bne-es-finetuned-augmented1
================================================


This model is a fine-tuned version of PlanTL-GOB-ES/longformer-base-4096-bne-es on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.7936
* Precision: 0.5307
* Recall: 0.6189
* F1: 0.5714
* Accuracy: 0.8447


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: 4
* eval\_batch\_size: 4
* 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 4.28.1
* Pytorch 2.0.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* 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 4.28.1
* Pytorch 2.0.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #longformer #token-classification #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: 4
* eval\_batch\_size: 4
* 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 4.28.1
* Pytorch 2.0.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3