---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: ModernBERT-large-hate-mr
  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-large-hate-mr

This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0005
- Accuracy: 1.0
- Precision: 1.0
- Recall: 1.0
- F1: 1.0

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.2742        | 1.0    | 31   | 0.6678          | 0.6      | 0.6349    | 0.5994 | 0.5715 |
| 1.1108        | 2.0    | 62   | 0.7303          | 0.5590   | 0.6745    | 0.5581 | 0.4701 |
| 1.024         | 3.0    | 93   | 0.6116          | 0.6795   | 0.7223    | 0.6800 | 0.6637 |
| 0.7994        | 4.0    | 124  | 0.6951          | 0.6506   | 0.7108    | 0.6500 | 0.6232 |
| 0.4984        | 5.0    | 155  | 0.8937          | 0.7012   | 0.7209    | 0.7008 | 0.6942 |
| 0.1153        | 6.0    | 186  | 1.4426          | 0.6940   | 0.7011    | 0.6942 | 0.6914 |
| 0.0718        | 7.0    | 217  | 1.2927          | 0.6988   | 0.6994    | 0.6989 | 0.6986 |
| 0.006         | 8.0    | 248  | 1.6155          | 0.7229   | 0.7262    | 0.7227 | 0.7218 |
| 0.0004        | 9.0    | 279  | 1.4752          | 0.7157   | 0.7173    | 0.7158 | 0.7152 |
| 0.0002        | 9.6885 | 300  | 1.4857          | 0.7205   | 0.7215    | 0.7206 | 0.7202 |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0