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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: DisambertSingleSense-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. -->
# DisambertSingleSense-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: 10.0010
- Precision: 0.6717
- Recall: 0.6486
- F1: 0.6599
- Matthews: 0.6479
## 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: 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: 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 | 641.2748 | 0.0 | 0.0 | 0.0 | -0.0000 |
| 4.9398 | 1.0 | 14014 | 7.1390 | 0.5863 | 0.5649 | 0.5754 | 0.5641 |
| 1.9762 | 2.0 | 28028 | 6.1541 | 0.6409 | 0.6117 | 0.6260 | 0.6110 |
| 1.1673 | 3.0 | 42042 | 6.2676 | 0.6534 | 0.6328 | 0.6429 | 0.6321 |
| 0.4893 | 4.0 | 56056 | 6.9641 | 0.6609 | 0.6394 | 0.6499 | 0.6387 |
| 0.2413 | 5.0 | 70070 | 7.8858 | 0.6637 | 0.6363 | 0.6497 | 0.6356 |
| 0.1245 | 6.0 | 84084 | 8.9750 | 0.6662 | 0.6310 | 0.6481 | 0.6304 |
| 0.0557 | 7.0 | 98098 | 9.4948 | 0.6693 | 0.6398 | 0.6542 | 0.6391 |
| 0.0451 | 8.0 | 112112 | 9.7435 | 0.6682 | 0.6402 | 0.6539 | 0.6395 |
| 0.0359 | 9.0 | 126126 | 9.9980 | 0.6676 | 0.6306 | 0.6486 | 0.6299 |
| 0.0188 | 10.0 | 140140 | 10.0010 | 0.6717 | 0.6486 | 0.6599 | 0.6479 |
### Framework versions
- Transformers 5.2.0
- Pytorch 2.6.0+cu124
- Datasets 4.5.0
- Tokenizers 0.22.2
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