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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
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