metadata
license: mit
tags:
- generated_from_trainer
datasets:
- dutch_social
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: robbert-twitter-sentiment
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: dutch_social
type: dutch_social
args: dutch_social
metrics:
- name: Accuracy
type: accuracy
value: 0.749
- name: F1
type: f1
value: 0.7491844724992662
- name: Precision
type: precision
value: 0.7493911755249737
- name: Recall
type: recall
value: 0.749
robbert-twitter-sentiment
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: 0.6818
- Accuracy: 0.749
- F1: 0.7492
- Precision: 0.7494
- Recall: 0.749
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.7485 | 1.0 | 188 | 0.7670 | 0.692 | 0.6915 | 0.6920 | 0.692 |
| 0.5202 | 2.0 | 376 | 0.6818 | 0.749 | 0.7492 | 0.7494 | 0.749 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cpu
- Datasets 2.0.0
- Tokenizers 0.12.0