robbert1010_lrate7.5b4
This model is a fine-tuned version of Tommert25/robbert0410_lrate7.5b4 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6951
- Precisions: 0.8407
- Recall: 0.8357
- F-measure: 0.8369
- Accuracy: 0.9176
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: 7.5e-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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
---|---|---|---|---|---|---|---|
0.3016 | 1.0 | 942 | 0.4329 | 0.8299 | 0.7433 | 0.7703 | 0.8953 |
0.2107 | 2.0 | 1884 | 0.5107 | 0.7934 | 0.7827 | 0.7878 | 0.9055 |
0.154 | 3.0 | 2826 | 0.7341 | 0.8129 | 0.7687 | 0.7758 | 0.8935 |
0.1198 | 4.0 | 3768 | 0.7313 | 0.7973 | 0.7394 | 0.7559 | 0.8993 |
0.0928 | 5.0 | 4710 | 0.6702 | 0.7996 | 0.7765 | 0.7824 | 0.8990 |
0.0529 | 6.0 | 5652 | 0.7075 | 0.8262 | 0.7983 | 0.8099 | 0.9106 |
0.039 | 7.0 | 6594 | 0.7946 | 0.8470 | 0.7670 | 0.7899 | 0.9087 |
0.0259 | 8.0 | 7536 | 0.6951 | 0.8407 | 0.8357 | 0.8369 | 0.9176 |
0.0203 | 9.0 | 8478 | 0.6762 | 0.8380 | 0.8210 | 0.8285 | 0.9206 |
0.0181 | 10.0 | 9420 | 0.6993 | 0.8384 | 0.8206 | 0.8289 | 0.9190 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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Model tree for Tommert25/robbert1010_lrate7.5b4
Base model
pdelobelle/robbert-v2-dutch-base
Finetuned
Tommert25/robbert0410_lrate7.5b4