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---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: answerdotai-ModernBERT-large-finetuned
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. -->
# answerdotai-ModernBERT-large-finetuned
This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0153
- Accuracy: 0.9980
- Precision: 0.9980
- Recall: 0.9980
- F1: 0.9980
## 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: 4.1905207188250686e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.0046 | 1.0 | 3011 | 0.0257 | 0.9962 | 0.9962 | 0.9962 | 0.9962 |
| 0.021 | 2.0 | 6022 | 0.0234 | 0.9959 | 0.9960 | 0.9959 | 0.9960 |
| 0.0001 | 3.0 | 9033 | 0.0194 | 0.9979 | 0.9978 | 0.9979 | 0.9978 |
| 0.0002 | 4.0 | 12044 | 0.0181 | 0.9979 | 0.9978 | 0.9979 | 0.9978 |
| 0.0 | 5.0 | 15055 | 0.0177 | 0.9980 | 0.9980 | 0.9980 | 0.9980 |
### Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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