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---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: Assignment4_Finetuned_ModernBERT_V2
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_Finetuned_ModernBERT_V2
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: 0.1926
- Accuracy: 0.9713
- F1: 0.9709
## 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 | F1 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 2.5497 | 0.2096 | 100 | 0.7948 | 0.7981 | 0.7867 |
| 0.514 | 0.4193 | 200 | 0.5135 | 0.8674 | 0.8618 |
| 0.3511 | 0.6289 | 300 | 0.4394 | 0.9 | 0.8968 |
| 0.2795 | 0.8386 | 400 | 0.3201 | 0.9258 | 0.9241 |
| 0.2055 | 1.0482 | 500 | 0.3262 | 0.9258 | 0.9248 |
| 0.1421 | 1.2579 | 600 | 0.3060 | 0.94 | 0.9391 |
| 0.1235 | 1.4675 | 700 | 0.3153 | 0.9352 | 0.9357 |
| 0.1166 | 1.6771 | 800 | 0.2892 | 0.9432 | 0.9427 |
| 0.0941 | 1.8868 | 900 | 0.2639 | 0.9513 | 0.9513 |
| 0.0832 | 2.0964 | 1000 | 0.2272 | 0.9587 | 0.9584 |
| 0.0331 | 2.3061 | 1100 | 0.2210 | 0.96 | 0.9596 |
| 0.0509 | 2.5157 | 1200 | 0.2112 | 0.9587 | 0.9582 |
| 0.023 | 2.7254 | 1300 | 0.2087 | 0.9597 | 0.9590 |
| 0.0206 | 2.9350 | 1400 | 0.2072 | 0.9645 | 0.9638 |
| 0.0194 | 3.1447 | 1500 | 0.1981 | 0.9639 | 0.9635 |
| 0.0101 | 3.3543 | 1600 | 0.1958 | 0.9697 | 0.9693 |
| 0.0052 | 3.5639 | 1700 | 0.2033 | 0.9687 | 0.9683 |
| 0.0056 | 3.7736 | 1800 | 0.1985 | 0.97 | 0.9696 |
| 0.0117 | 3.9832 | 1900 | 0.1914 | 0.9716 | 0.9713 |
| 0.0021 | 4.1929 | 2000 | 0.1910 | 0.9719 | 0.9716 |
| 0.0015 | 4.4025 | 2100 | 0.1916 | 0.9716 | 0.9712 |
| 0.0024 | 4.6122 | 2200 | 0.1926 | 0.9713 | 0.9709 |
| 0.0008 | 4.8218 | 2300 | 0.1926 | 0.9713 | 0.9709 |
### Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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