File size: 2,127 Bytes
0545db9 e142bac 0545db9 e142bac 0545db9 e142bac 0545db9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 |
---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: robbert-v2-dutch-base-finetuned-sentiment
results: []
---
<!-- 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. -->
# robbert-v2-dutch-base-finetuned-sentiment
This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2055
- Accuracy: 0.3673
- F1: 0.3712
## 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: 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.0698 | 1.0 | 86 | 1.0615 | 0.4898 | 0.3314 |
| 1.0312 | 2.0 | 172 | 1.0980 | 0.4052 | 0.3792 |
| 0.9602 | 3.0 | 258 | 1.2286 | 0.4169 | 0.3583 |
| 0.8644 | 4.0 | 344 | 1.2476 | 0.4315 | 0.3893 |
| 0.7201 | 5.0 | 430 | 1.4700 | 0.4227 | 0.3993 |
| 0.5759 | 6.0 | 516 | 1.6862 | 0.3848 | 0.3821 |
| 0.477 | 7.0 | 602 | 1.9556 | 0.3469 | 0.3529 |
| 0.3852 | 8.0 | 688 | 2.0945 | 0.3586 | 0.3637 |
| 0.3377 | 9.0 | 774 | 2.1969 | 0.3440 | 0.3502 |
| 0.2965 | 10.0 | 860 | 2.2055 | 0.3673 | 0.3712 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|