---
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: 0.8739
- F1: 0.8061
- Accuracy: 0.8082

## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | F1     | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:------:|:--------:|
| 4.0021        | 1.0     | 19   | 1.9146          | 0.0636 | 0.1469   |
| 3.6752        | 2.0     | 38   | 1.7785          | 0.3022 | 0.3388   |
| 3.2521        | 3.0     | 57   | 1.4559          | 0.4311 | 0.4735   |
| 2.6907        | 4.0     | 76   | 1.1927          | 0.5475 | 0.5714   |
| 2.2003        | 5.0     | 95   | 0.9852          | 0.6614 | 0.6571   |
| 1.7928        | 6.0     | 114  | 0.8017          | 0.7147 | 0.7102   |
| 1.4909        | 7.0     | 133  | 0.8603          | 0.7070 | 0.7020   |
| 1.3136        | 8.0     | 152  | 0.6970          | 0.7395 | 0.7429   |
| 1.1483        | 9.0     | 171  | 0.5679          | 0.7774 | 0.7755   |
| 0.903         | 10.0    | 190  | 0.9122          | 0.7078 | 0.7061   |
| 0.886         | 11.0    | 209  | 0.6270          | 0.7707 | 0.7755   |
| 0.7609        | 12.0    | 228  | 0.6756          | 0.8038 | 0.8082   |
| 0.6929        | 13.0    | 247  | 0.5790          | 0.8290 | 0.8327   |
| 0.4927        | 14.0    | 266  | 0.7072          | 0.8067 | 0.8082   |
| 0.3282        | 15.0    | 285  | 0.6293          | 0.8490 | 0.8490   |
| 0.2706        | 16.0    | 304  | 0.8920          | 0.7867 | 0.7878   |
| 0.2311        | 17.0    | 323  | 0.7759          | 0.8466 | 0.8490   |
| 0.1268        | 18.0    | 342  | 0.7496          | 0.8324 | 0.8327   |
| 0.1276        | 18.9730 | 360  | 0.8739          | 0.8061 | 0.8082   |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.21.0