File size: 2,248 Bytes
dcf6d9e |
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:
- recall
- accuracy
model-index:
- name: robbert0410_lrate10b16
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. -->
# robbert0410_lrate10b16
This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4783
- Precisions: 0.8324
- Recall: 0.8123
- F-measure: 0.8208
- Accuracy: 0.9164
## 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: 0.0001
- 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: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.6379 | 1.0 | 236 | 0.4156 | 0.8657 | 0.6790 | 0.6955 | 0.8798 |
| 0.3257 | 2.0 | 472 | 0.3378 | 0.7529 | 0.7397 | 0.7336 | 0.8932 |
| 0.1977 | 3.0 | 708 | 0.3737 | 0.7960 | 0.7383 | 0.7451 | 0.9003 |
| 0.1197 | 4.0 | 944 | 0.4060 | 0.8446 | 0.7503 | 0.7696 | 0.9025 |
| 0.0659 | 5.0 | 1180 | 0.4428 | 0.7851 | 0.7731 | 0.7779 | 0.9063 |
| 0.0447 | 6.0 | 1416 | 0.4972 | 0.8285 | 0.7991 | 0.8124 | 0.9127 |
| 0.0256 | 7.0 | 1652 | 0.4783 | 0.8324 | 0.8123 | 0.8208 | 0.9164 |
| 0.0173 | 8.0 | 1888 | 0.4918 | 0.8251 | 0.8082 | 0.8159 | 0.9169 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
|