---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ModernBERT-base_nli
  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-base_nli

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: 3.4416
- Accuracy: 0.5623
- Precision Macro: 0.5618
- Recall Macro: 0.5627
- F1 Macro: 0.5621
- F1 Weighted: 0.5617

## 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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1 Macro | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:-----------:|
| 2.164         | 1.0   | 72   | 1.0434          | 0.4483   | 0.4472          | 0.4484       | 0.4398   | 0.4395      |
| 2.0623        | 2.0   | 144  | 0.9968          | 0.4984   | 0.5026          | 0.4994       | 0.4983   | 0.4978      |
| 1.8507        | 3.0   | 216  | 1.0155          | 0.5016   | 0.5522          | 0.5034       | 0.4808   | 0.4802      |
| 1.7076        | 4.0   | 288  | 0.9344          | 0.5721   | 0.5902          | 0.5738       | 0.5572   | 0.5563      |
| 1.4431        | 5.0   | 360  | 0.9258          | 0.5756   | 0.5770          | 0.5768       | 0.5719   | 0.5714      |
| 1.1592        | 6.0   | 432  | 1.0425          | 0.5738   | 0.5831          | 0.5740       | 0.5693   | 0.5691      |
| 0.6916        | 7.0   | 504  | 1.2622          | 0.5659   | 0.5711          | 0.5670       | 0.5640   | 0.5636      |
| 0.3547        | 8.0   | 576  | 1.7560          | 0.5455   | 0.5495          | 0.5452       | 0.5460   | 0.5459      |
| 0.2534        | 9.0   | 648  | 2.1882          | 0.5494   | 0.5620          | 0.5515       | 0.5409   | 0.5401      |
| 0.1018        | 10.0  | 720  | 2.3462          | 0.5645   | 0.5641          | 0.5652       | 0.5633   | 0.5630      |
| 0.0931        | 11.0  | 792  | 2.6256          | 0.5565   | 0.5619          | 0.5582       | 0.5483   | 0.5475      |
| 0.0504        | 12.0  | 864  | 2.7252          | 0.5552   | 0.5570          | 0.5557       | 0.5555   | 0.5551      |
| 0.0379        | 13.0  | 936  | 2.9577          | 0.5517   | 0.5518          | 0.5521       | 0.5518   | 0.5515      |
| 0.0111        | 14.0  | 1008 | 3.2048          | 0.5614   | 0.5621          | 0.5621       | 0.5609   | 0.5604      |
| 0.0018        | 15.0  | 1080 | 3.3005          | 0.5610   | 0.5621          | 0.5612       | 0.5616   | 0.5613      |
| 0.0003        | 16.0  | 1152 | 3.3958          | 0.5610   | 0.5602          | 0.5615       | 0.5605   | 0.5601      |
| 0.0001        | 17.0  | 1224 | 3.4259          | 0.5623   | 0.5617          | 0.5628       | 0.5620   | 0.5617      |
| 0.0001        | 18.0  | 1296 | 3.4368          | 0.5619   | 0.5613          | 0.5623       | 0.5616   | 0.5612      |
| 0.0001        | 19.0  | 1368 | 3.4412          | 0.5619   | 0.5614          | 0.5623       | 0.5616   | 0.5613      |
| 0.0001        | 20.0  | 1440 | 3.4416          | 0.5623   | 0.5618          | 0.5627       | 0.5621   | 0.5617      |


### Framework versions

- Transformers 4.55.0
- Pytorch 2.7.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4