
---

<!-- 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. -->

# bert-swe-skills-ner

This model is a fine-tuned version of [RJuro/bert-swe-skills-ner](https://huggingface.co/RJuro/bert-swe-skills-ner) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0486
- Precision: 0.8194
- Recall: 0.8710
- F1: 0.8444
- Accuracy: 0.9856

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 39   | 0.1509          | 0.5872    | 0.6636 | 0.6231 | 0.9492   |
| No log        | 2.0   | 78   | 0.1069          | 0.6750    | 0.7544 | 0.7125 | 0.9660   |
| No log        | 3.0   | 117  | 0.0688          | 0.7692    | 0.8050 | 0.7867 | 0.9785   |
| No log        | 4.0   | 156  | 0.0529          | 0.8239    | 0.8452 | 0.8344 | 0.9842   |
| No log        | 5.0   | 195  | 0.0486          | 0.8194    | 0.8710 | 0.8444 | 0.9856   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "widget": [{"text": "Du \u00e4r legitimerad grundskolel\u00e4rare med aktuell beh\u00f6righet. Personliga egenskaper: F\u00f6r att lyckas och trivas hos oss beh\u00f6ver du ha god f\u00f6rm\u00e5ga att samarbeta, vara lyh\u00f6rd och ha l\u00e4tt f\u00f6r att s\u00e4tta dig in i andra m\u00e4nniskors perspektiv. Du beh\u00f6ver vara trygg i dig sj\u00e4lv, stabil och ha god sj\u00e4lvinsikt. Det \u00e4r viktigt i rollen att du har en v\u00e4l utvecklad pedagogisk f\u00f6rm\u00e5ga. Du har god f\u00f6rst\u00e5else f\u00f6r hur barn och ungdomar tar till sig kunskap och om olika f\u00f6ruts\u00e4ttningar f\u00f6r l\u00e4rande. Det \u00e4r ocks\u00e5 viktigt att du \u00e4r flexibel och l\u00e4tt kan anpassa dig till \u00e4ndrade omst\u00e4ndigheter i verksamheten."}], "model-index": [{"name": "bert-swe-skills-ner", "results": []}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 



---


bert-swe-skills-ner
===================


This model is a fine-tuned version of RJuro/bert-swe-skills-ner on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0486
* Precision: 0.8194
* Recall: 0.8710
* F1: 0.8444
* Accuracy: 0.9856


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: 5


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3



### 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: 5 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #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: 5 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #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: 5### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3