---
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