---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Assignment4_Distilled_ModernBERT
  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. -->

# Assignment4_Distilled_ModernBERT

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: 0.2589
- Accuracy: 0.9681

## 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: 6e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 7.8963        | 0.2096 | 100  | 2.9564          | 0.7577   |
| 1.6375        | 0.4193 | 200  | 1.0919          | 0.8806   |
| 0.8239        | 0.6289 | 300  | 0.6403          | 0.9335   |
| 0.5738        | 0.8386 | 400  | 0.5019          | 0.9448   |
| 0.3915        | 1.0482 | 500  | 0.4918          | 0.9452   |
| 0.1938        | 1.2579 | 600  | 0.4370          | 0.9548   |
| 0.2045        | 1.4675 | 700  | 0.4937          | 0.9435   |
| 0.1874        | 1.6771 | 800  | 0.4477          | 0.9568   |
| 0.1804        | 1.8868 | 900  | 0.4118          | 0.9581   |
| 0.1237        | 2.0964 | 1000 | 0.3573          | 0.9616   |
| 0.076         | 2.3061 | 1100 | 0.3772          | 0.9574   |
| 0.0834        | 2.5157 | 1200 | 0.3337          | 0.9652   |
| 0.0713        | 2.7254 | 1300 | 0.3032          | 0.9658   |
| 0.0514        | 2.9350 | 1400 | 0.3009          | 0.9661   |
| 0.0448        | 3.1447 | 1500 | 0.2892          | 0.9661   |
| 0.0425        | 3.3543 | 1600 | 0.2864          | 0.9671   |
| 0.0341        | 3.5639 | 1700 | 0.2859          | 0.9642   |
| 0.0389        | 3.7736 | 1800 | 0.2763          | 0.9677   |
| 0.0409        | 3.9832 | 1900 | 0.2682          | 0.9668   |
| 0.0266        | 4.1929 | 2000 | 0.2624          | 0.9674   |
| 0.0265        | 4.4025 | 2100 | 0.2610          | 0.9684   |
| 0.0267        | 4.6122 | 2200 | 0.2592          | 0.9684   |
| 0.027         | 4.8218 | 2300 | 0.2589          | 0.9681   |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1