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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
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 semcor dataset.
It achieves the following results on the evaluation set:
- Loss: 13.9274
- Precision: 0.6274
- Recall: 0.6398
- F1: 0.6335
- Matthews: 0.6392
## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- 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: inverse_sqrt
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Matthews |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 0 | 0 | 427.8458 | 0.5014 | 0.4790 | 0.4899 | 0.4781 |
| 9.0689 | 1.0 | 3504 | 15.5744 | 0.6010 | 0.6196 | 0.6102 | 0.6190 |
| 8.5420 | 2.0 | 7008 | 15.4129 | 0.6088 | 0.6253 | 0.6170 | 0.6247 |
| 7.8106 | 3.0 | 10512 | 14.3562 | 0.6138 | 0.6328 | 0.6232 | 0.6322 |
| 7.6303 | 4.0 | 14016 | 13.9741 | 0.6157 | 0.6372 | 0.6262 | 0.6366 |
| 7.6930 | 5.0 | 17520 | 13.8324 | 0.6262 | 0.6402 | 0.6331 | 0.6397 |
| 7.4897 | 6.0 | 21024 | 13.9649 | 0.6144 | 0.6323 | 0.6232 | 0.6318 |
| 7.3819 | 7.0 | 24528 | 13.4877 | 0.6273 | 0.6407 | 0.6339 | 0.6401 |
| 7.4083 | 8.0 | 28032 | 13.7249 | 0.6321 | 0.6402 | 0.6362 | 0.6397 |
| 7.0140 | 9.0 | 31536 | 13.5219 | 0.6168 | 0.6389 | 0.6277 | 0.6383 |
| 7.7287 | 10.0 | 35040 | 13.9274 | 0.6274 | 0.6398 | 0.6335 | 0.6392 |
### Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2
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