
<!-- 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-finetuned-protagonist-english

This model is a fine-tuned version of [Jean-Baptiste/roberta-large-ner-english](https://huggingface.co/Jean-Baptiste/roberta-large-ner-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0630
- Precision: 0.8646
- Recall: 0.8839
- F1: 0.8742
- Accuracy: 0.9876

## 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   | 25   | 0.0659          | 0.8860    | 0.9018 | 0.8938 | 0.9862   |
| No log        | 2.0   | 50   | 0.0583          | 0.8553    | 0.8705 | 0.8628 | 0.9860   |
| No log        | 3.0   | 75   | 0.0593          | 0.8728    | 0.8884 | 0.8805 | 0.9876   |
| No log        | 4.0   | 100  | 0.0622          | 0.8559    | 0.875  | 0.8653 | 0.9871   |
| No log        | 5.0   | 125  | 0.0630          | 0.8646    | 0.8839 | 0.8742 | 0.9876   |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.2+cu102
- Datasets 2.2.1
- Tokenizers 0.11.0

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "bert-finetuned-protagonist-english", "results": []}]}
transformers pytorch roberta token-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

bert-finetuned-protagonist-english
==================================


This model is a fine-tuned version of Jean-Baptiste/roberta-large-ner-english on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0630
* Precision: 0.8646
* Recall: 0.8839
* F1: 0.8742
* Accuracy: 0.9876


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 4.16.2
* Pytorch 1.10.2+cu102
* Datasets 2.2.1
* Tokenizers 0.11.0



### 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 4.16.2
* Pytorch 1.10.2+cu102
* Datasets 2.2.1
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #roberta #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 4.16.2
* Pytorch 1.10.2+cu102
* Datasets 2.2.1
* Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #roberta #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 4.16.2
* Pytorch 1.10.2+cu102
* Datasets 2.2.1
* Tokenizers 0.11.0