File size: 2,212 Bytes
d10da3b dfe1df7 d10da3b dfe1df7 d10da3b dfe1df7 d10da3b dfe1df7 d10da3b |
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 |
---
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: acer_nitro_bert_turk
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. -->
# acer_nitro_bert_turk
This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3791
- F1: 0.8532
- Roc Auc: 0.9236
- Accuracy: 0.7108
## 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: 2
- eval_batch_size: 2
- 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 | F1 | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log | 1.0 | 166 | 0.3705 | 0.8426 | 0.9139 | 0.7229 |
| No log | 2.0 | 332 | 0.3450 | 0.8584 | 0.9380 | 0.7470 |
| No log | 3.0 | 498 | 0.3661 | 0.8491 | 0.9128 | 0.7108 |
| 0.0532 | 4.0 | 664 | 0.3745 | 0.8558 | 0.9213 | 0.7229 |
| 0.0532 | 5.0 | 830 | 0.3598 | 0.8571 | 0.9249 | 0.7349 |
| 0.0532 | 6.0 | 996 | 0.3747 | 0.8571 | 0.9249 | 0.7229 |
| 0.0219 | 7.0 | 1162 | 0.3540 | 0.8624 | 0.9297 | 0.7349 |
| 0.0219 | 8.0 | 1328 | 0.3761 | 0.8584 | 0.9285 | 0.7229 |
| 0.0219 | 9.0 | 1494 | 0.3836 | 0.8493 | 0.9223 | 0.7108 |
| 0.0108 | 10.0 | 1660 | 0.3791 | 0.8532 | 0.9236 | 0.7108 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
|