---
library_name: transformers
base_model: CocoRoF/ModernBERT-SimCSE-multitask_v03-distill
tags:
- generated_from_trainer
model-index:
- name: ModernBERT_category
  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_category

This model is a fine-tuned version of [CocoRoF/ModernBERT-SimCSE-multitask_v03-distill](https://huggingface.co/CocoRoF/ModernBERT-SimCSE-multitask_v03-distill) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3204

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 32
- total_train_batch_size: 1024
- total_eval_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 15.608        | 0.0444 | 1000  | 0.4726          |
| 14.207        | 0.0888 | 2000  | 0.4257          |
| 12.9331       | 0.1331 | 3000  | 0.4045          |
| 12.5004       | 0.1775 | 4000  | 0.3896          |
| 12.5729       | 0.2219 | 5000  | 0.3786          |
| 12.2146       | 0.2663 | 6000  | 0.3713          |
| 11.8243       | 0.3107 | 7000  | 0.3632          |
| 11.3651       | 0.3550 | 8000  | 0.3578          |
| 11.7742       | 0.3994 | 9000  | 0.3524          |
| 11.022        | 0.4438 | 10000 | 0.3483          |
| 10.871        | 0.4882 | 11000 | 0.3453          |
| 11.24         | 0.5326 | 12000 | 0.3404          |
| 10.6222       | 0.5769 | 13000 | 0.3380          |
| 10.9927       | 0.6213 | 14000 | 0.3354          |
| 10.8912       | 0.6657 | 15000 | 0.3330          |
| 10.7683       | 0.7101 | 16000 | 0.3311          |
| 10.4059       | 0.7545 | 17000 | 0.3286          |
| 10.4617       | 0.7988 | 18000 | 0.3258          |
| 10.5632       | 0.8432 | 19000 | 0.3247          |
| 9.9193        | 0.8876 | 20000 | 0.3231          |
| 9.7854        | 0.9320 | 21000 | 0.3205          |
| 10.3546       | 0.9764 | 22000 | 0.3204          |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0