---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: pangolin-large
  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. -->

# pangolin-large

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: 0.0225
- F1: 0.9904
- Accuracy: 0.9937

## 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: 64
- eval_batch_size: 32
- 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: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | F1     | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:------:|:--------:|
| 0.1519        | 0.1042 | 100  | 0.1354          | 0.9229 | 0.9534   |
| 0.068         | 0.2083 | 200  | 0.0553          | 0.9689 | 0.9797   |
| 0.0458        | 0.3125 | 300  | 0.0555          | 0.9758 | 0.9844   |
| 0.0389        | 0.4167 | 400  | 0.0442          | 0.9804 | 0.9874   |
| 0.04          | 0.5208 | 500  | 0.0323          | 0.9842 | 0.9897   |
| 0.0308        | 0.625  | 600  | 0.0357          | 0.9836 | 0.9894   |
| 0.0357        | 0.7292 | 700  | 0.0336          | 0.9861 | 0.9909   |
| 0.0306        | 0.8333 | 800  | 0.0299          | 0.9880 | 0.9921   |
| 0.0246        | 0.9375 | 900  | 0.0338          | 0.9846 | 0.9900   |
| 0.0195        | 1.0417 | 1000 | 0.0260          | 0.9881 | 0.9922   |
| 0.0124        | 1.1458 | 1100 | 0.0225          | 0.9887 | 0.9926   |
| 0.005         | 1.25   | 1200 | 0.0286          | 0.9874 | 0.9917   |
| 0.0075        | 1.3542 | 1300 | 0.0313          | 0.9897 | 0.9933   |
| 0.0065        | 1.4583 | 1400 | 0.0318          | 0.9892 | 0.9930   |
| 0.0093        | 1.5625 | 1500 | 0.0257          | 0.9903 | 0.9937   |
| 0.0099        | 1.6667 | 1600 | 0.0233          | 0.9889 | 0.9927   |
| 0.0054        | 1.7708 | 1700 | 0.0221          | 0.9905 | 0.9938   |
| 0.0077        | 1.875  | 1800 | 0.0222          | 0.9907 | 0.9939   |
| 0.0052        | 1.9792 | 1900 | 0.0225          | 0.9904 | 0.9937   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0