File size: 2,028 Bytes
290d2f4 c2d56d3 290d2f4 7495f75 a6c88ca 290d2f4 a6c88ca 7495f75 7c31eee 16cdc26 290d2f4 c2d56d3 290d2f4 |
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 |
---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: modernbert-tr-classifier
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. -->
# modernbert-tr-classifier
This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7290
- F1: 0.8554
- Accuracy: 0.8537
## 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: 8e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- optimizer: Use adamw_torch with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
| 3.704 | 1.0 | 19 | 1.4201 | 0.4022 | 0.4553 |
| 2.3894 | 2.0 | 38 | 0.9204 | 0.6456 | 0.6423 |
| 1.4461 | 3.0 | 57 | 0.5806 | 0.8250 | 0.8211 |
| 0.9515 | 4.0 | 76 | 0.4542 | 0.8714 | 0.8699 |
| 0.585 | 5.0 | 95 | 0.4316 | 0.8862 | 0.8862 |
| 0.3665 | 6.0 | 114 | 0.5989 | 0.8533 | 0.8537 |
| 0.1882 | 7.0 | 133 | 0.7290 | 0.8554 | 0.8537 |
### Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.21.0
|