File size: 2,820 Bytes
2a22438 |
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 73 74 75 76 77 78 |
---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert_seed37_1311
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_seed37_1311
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: 0.3848
- Precisions: 0.8521
- Recall: 0.8198
- F-measure: 0.8327
- Accuracy: 0.9441
## 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: 16
- eval_batch_size: 16
- seed: 37
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 14
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.4569 | 1.0 | 236 | 0.2571 | 0.7110 | 0.7130 | 0.7092 | 0.9217 |
| 0.222 | 2.0 | 472 | 0.2286 | 0.7904 | 0.7574 | 0.7685 | 0.9313 |
| 0.1311 | 3.0 | 708 | 0.2412 | 0.8047 | 0.7810 | 0.7875 | 0.9359 |
| 0.0813 | 4.0 | 944 | 0.2755 | 0.8019 | 0.7775 | 0.7886 | 0.9354 |
| 0.0552 | 5.0 | 1180 | 0.3120 | 0.8499 | 0.7793 | 0.8032 | 0.9409 |
| 0.0323 | 6.0 | 1416 | 0.3536 | 0.8350 | 0.7955 | 0.8099 | 0.9402 |
| 0.0212 | 7.0 | 1652 | 0.3789 | 0.8448 | 0.7817 | 0.8092 | 0.9405 |
| 0.0154 | 8.0 | 1888 | 0.3835 | 0.8419 | 0.7780 | 0.7971 | 0.9385 |
| 0.0119 | 9.0 | 2124 | 0.3906 | 0.8583 | 0.7812 | 0.8058 | 0.9388 |
| 0.0081 | 10.0 | 2360 | 0.3910 | 0.8477 | 0.7874 | 0.8062 | 0.9424 |
| 0.0052 | 11.0 | 2596 | 0.3839 | 0.8642 | 0.8087 | 0.8298 | 0.9431 |
| 0.0046 | 12.0 | 2832 | 0.3848 | 0.8521 | 0.8198 | 0.8327 | 0.9441 |
| 0.0018 | 13.0 | 3068 | 0.4017 | 0.8450 | 0.8125 | 0.8240 | 0.9438 |
| 0.0014 | 14.0 | 3304 | 0.4060 | 0.8571 | 0.8088 | 0.8265 | 0.9441 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
|