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# longformer-base-4096-bne-es-finetuned-v2

This model is a fine-tuned version of [joheras/longformer-base-4096-bne-es-finetuned-clinais](https://huggingface.co/joheras/longformer-base-4096-bne-es-finetuned-clinais) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0205
- Precision: 0.4420
- Recall: 0.6075
- F1: 0.5117
- Accuracy: 0.8420

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 196  | 0.6855          | 0.1500    | 0.2840 | 0.1963 | 0.7991   |
| No log        | 2.0   | 392  | 0.5677          | 0.2372    | 0.3962 | 0.2967 | 0.8271   |
| 0.7365        | 3.0   | 588  | 0.5457          | 0.3043    | 0.5142 | 0.3823 | 0.8412   |
| 0.7365        | 4.0   | 784  | 0.5818          | 0.3268    | 0.5208 | 0.4016 | 0.8303   |
| 0.7365        | 5.0   | 980  | 0.5958          | 0.3595    | 0.5538 | 0.4359 | 0.8385   |
| 0.3443        | 6.0   | 1176 | 0.6380          | 0.3916    | 0.5660 | 0.4630 | 0.8396   |
| 0.3443        | 7.0   | 1372 | 0.6835          | 0.3499    | 0.5594 | 0.4305 | 0.8272   |
| 0.2031        | 8.0   | 1568 | 0.6758          | 0.4088    | 0.5726 | 0.4770 | 0.8441   |
| 0.2031        | 9.0   | 1764 | 0.7236          | 0.3921    | 0.5792 | 0.4676 | 0.8397   |
| 0.2031        | 10.0  | 1960 | 0.7699          | 0.3941    | 0.5755 | 0.4678 | 0.8349   |
| 0.1283        | 11.0  | 2156 | 0.7788          | 0.4004    | 0.5745 | 0.4719 | 0.8315   |
| 0.1283        | 12.0  | 2352 | 0.7802          | 0.4164    | 0.6019 | 0.4923 | 0.8479   |
| 0.0861        | 13.0  | 2548 | 0.8092          | 0.4280    | 0.5915 | 0.4966 | 0.8394   |
| 0.0861        | 14.0  | 2744 | 0.8582          | 0.4211    | 0.5991 | 0.4945 | 0.8373   |
| 0.0861        | 15.0  | 2940 | 0.8581          | 0.3860    | 0.5925 | 0.4674 | 0.8407   |
| 0.0589        | 16.0  | 3136 | 0.9137          | 0.4213    | 0.6038 | 0.4963 | 0.8291   |
| 0.0589        | 17.0  | 3332 | 0.8669          | 0.4287    | 0.6038 | 0.5014 | 0.8448   |
| 0.0436        | 18.0  | 3528 | 0.8987          | 0.4365    | 0.6028 | 0.5063 | 0.8403   |
| 0.0436        | 19.0  | 3724 | 0.9389          | 0.4437    | 0.5991 | 0.5098 | 0.8360   |
| 0.0436        | 20.0  | 3920 | 0.9512          | 0.4479    | 0.6    | 0.5129 | 0.8348   |
| 0.0313        | 21.0  | 4116 | 0.9484          | 0.4535    | 0.6075 | 0.5194 | 0.8445   |
| 0.0313        | 22.0  | 4312 | 0.9715          | 0.4498    | 0.6123 | 0.5186 | 0.8438   |
| 0.0236        | 23.0  | 4508 | 0.9726          | 0.4542    | 0.6170 | 0.5232 | 0.8457   |
| 0.0236        | 24.0  | 4704 | 0.9586          | 0.4531    | 0.6066 | 0.5188 | 0.8427   |
| 0.0236        | 25.0  | 4900 | 0.9962          | 0.4634    | 0.6160 | 0.5290 | 0.8433   |
| 0.0206        | 26.0  | 5096 | 1.0098          | 0.4683    | 0.6198 | 0.5335 | 0.8429   |
| 0.0206        | 27.0  | 5292 | 0.9914          | 0.4527    | 0.6094 | 0.5195 | 0.8414   |
| 0.0206        | 28.0  | 5488 | 1.0146          | 0.4567    | 0.6113 | 0.5228 | 0.8436   |
| 0.0154        | 29.0  | 5684 | 1.0199          | 0.4468    | 0.6104 | 0.5159 | 0.8428   |
| 0.0154        | 30.0  | 5880 | 1.0205          | 0.4420    | 0.6075 | 0.5117 | 0.8420   |


### 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-v2", "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-v2
========================================


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


* Loss: 1.0205
* Precision: 0.4420
* Recall: 0.6075
* F1: 0.5117
* Accuracy: 0.8420


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: 30


### 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: 30 ### 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: 30 ### Training results ### Framework versions


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