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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
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