---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
model-index:
- name: modernbert-large-docx
  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-docx

This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5145

## 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: 2
- eval_batch_size: 1
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 148
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.5541        | 0.1686 | 100  | 0.5688          |
| 0.5465        | 0.3373 | 200  | 0.5476          |
| 0.5054        | 0.5059 | 300  | 0.5369          |
| 0.5113        | 0.6745 | 400  | 0.5335          |
| 0.5281        | 0.8432 | 500  | 0.5354          |
| 0.5441        | 1.0118 | 600  | 0.5312          |
| 0.4983        | 1.1804 | 700  | 0.5269          |
| 0.5151        | 1.3491 | 800  | 0.5257          |
| 0.5247        | 1.5177 | 900  | 0.5258          |
| 0.5212        | 1.6863 | 1000 | 0.5343          |
| 0.5243        | 1.8550 | 1100 | 0.5190          |
| 0.5007        | 2.0236 | 1200 | 0.5206          |
| 0.4971        | 2.1922 | 1300 | 0.5260          |
| 0.504         | 2.3609 | 1400 | 0.5264          |
| 0.5152        | 2.5295 | 1500 | 0.5229          |
| 0.5269        | 2.6981 | 1600 | 0.5264          |
| 0.5202        | 2.8668 | 1700 | 0.5282          |
| 0.5117        | 3.0354 | 1800 | 0.5179          |
| 0.5163        | 3.2040 | 1900 | 0.5168          |
| 0.4929        | 3.3727 | 2000 | 0.5165          |
| 0.5017        | 3.5413 | 2100 | 0.5151          |
| 0.5031        | 3.7099 | 2200 | 0.5155          |
| 0.52          | 3.8786 | 2300 | 0.5155          |
| 0.5055        | 4.0472 | 2400 | 0.5143          |
| 0.4968        | 4.2159 | 2500 | 0.5138          |
| 0.4868        | 4.3845 | 2600 | 0.5147          |
| 0.4888        | 4.5531 | 2700 | 0.5145          |
| 0.4994        | 4.7218 | 2800 | 0.5145          |
| 0.4911        | 4.8904 | 2900 | 0.5145          |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.1