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# robbert-twitter-sentiment-tokenized

This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on the dutch_social dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5473
- Accuracy: 0.814
- F1: 0.8133
- Precision: 0.8131
- Recall: 0.814

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6895        | 1.0   | 282  | 0.6307          | 0.7433   | 0.7442 | 0.7500    | 0.7433 |
| 0.4948        | 2.0   | 564  | 0.5189          | 0.8053   | 0.8062 | 0.8081    | 0.8053 |
| 0.2642        | 3.0   | 846  | 0.5473          | 0.814    | 0.8133 | 0.8131    | 0.814  |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0+cpu
- Datasets 2.0.0
- Tokenizers 0.11.6

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["dutch_social"], "metrics": ["accuracy", "f1", "precision", "recall"], "model-index": [{"name": "robbert-twitter-sentiment-tokenized", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "dutch_social", "type": "dutch_social", "args": "dutch_social"}, "metrics": [{"type": "accuracy", "value": 0.814, "name": "Accuracy"}, {"type": "f1", "value": 0.8132800039281481, "name": "F1"}, {"type": "precision", "value": 0.8131073640029836, "name": "Precision"}, {"type": "recall", "value": 0.814, "name": "Recall"}]}]}]}
transformers pytorch roberta text-classification generated_from_trainer dataset:dutch_social license:mit model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #dataset-dutch_social #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 

robbert-twitter-sentiment-tokenized
===================================


This model is a fine-tuned version of pdelobelle/robbert-v2-dutch-base on the dutch\_social dataset.
It achieves the following results on the evaluation set:


* Loss: 0.5473
* Accuracy: 0.814
* F1: 0.8133
* Precision: 0.8131
* Recall: 0.814


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: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3


### Training results



### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cpu
* Datasets 2.0.0
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cpu
* Datasets 2.0.0
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #dataset-dutch_social #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cpu
* Datasets 2.0.0
* Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #dataset-dutch_social #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3### Training results### Framework versions


* Transformers 4.17.0
* Pytorch 1.11.0+cpu
* Datasets 2.0.0
* Tokenizers 0.11.6