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library_name: transformers
language:
- en
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
- matthews_correlation
model-index:
- name: DisamBertCrossEncoder-base
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. -->
# DisamBertCrossEncoder-base
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: 0.3160
- Precision: 0.6783
- Recall: 0.5978
- F1: 0.6355
- Accuracy: 0.9378
- Matthews Correlation: 0.6031
## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 320
- 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Matthews Correlation |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|:--------------------:|
| No log | 0 | 0 | 1123.2456 | 0.0907 | 1.0 | 0.1663 | 0.0909 | 0.0045 |
| 0.1943 | 1.0 | 9050 | 0.1832 | 0.7346 | 0.2615 | 0.3857 | 0.9245 | 0.4096 |
| 0.1500 | 2.0 | 18100 | 0.1551 | 0.7019 | 0.4967 | 0.5817 | 0.9352 | 0.5574 |
| 0.1242 | 3.0 | 27150 | 0.1481 | 0.7381 | 0.5451 | 0.6271 | 0.9412 | 0.6040 |
| 0.1017 | 4.0 | 36200 | 0.1482 | 0.7413 | 0.5604 | 0.6383 | 0.9424 | 0.6147 |
| 0.0774 | 5.0 | 45250 | 0.1564 | 0.7179 | 0.6154 | 0.6627 | 0.9432 | 0.6342 |
| 0.0610 | 6.0 | 54300 | 0.1859 | 0.7579 | 0.5297 | 0.6235 | 0.9420 | 0.6044 |
| 0.0434 | 7.0 | 63350 | 0.2016 | 0.6754 | 0.6264 | 0.6499 | 0.9388 | 0.6170 |
| 0.0298 | 8.0 | 72400 | 0.2480 | 0.6520 | 0.6505 | 0.6513 | 0.9368 | 0.6165 |
| 0.0216 | 9.0 | 81450 | 0.2961 | 0.6819 | 0.5890 | 0.6321 | 0.9378 | 0.6002 |
| 0.0174 | 10.0 | 90500 | 0.3160 | 0.6783 | 0.5978 | 0.6355 | 0.9378 | 0.6031 |
### Framework versions
- Transformers 5.3.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2
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