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---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: modernbert-acceptance-classifier-final
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. -->
# modernbert-acceptance-classifier-final
This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6494
- F1: 0.8156
- Precision: 0.8160
- Recall: 0.8157
## 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: 1.2448932804037876e-05
- train_batch_size: 10
- eval_batch_size: 8
- 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
- lr_scheduler_warmup_ratio: 0.17030843157226483
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
| 0.4105 | 1.0 | 1609 | 0.3929 | 0.8180 | 0.8180 | 0.8180 |
| 0.375 | 2.0 | 3218 | 0.4030 | 0.8222 | 0.8262 | 0.8229 |
| 0.185 | 3.0 | 4827 | 0.6494 | 0.8156 | 0.8160 | 0.8157 |
### Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.2.2
- Datasets 3.1.0
- Tokenizers 0.21.0
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