---
library_name: peft
license: apache-2.0
base_model: google-bert/bert-base-cased
tags:
- generated_from_trainer
model-index:
- name: marvelous-pug-454
  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. -->

# marvelous-pug-454

This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4049
- Hamming Loss: 0.1123
- Zero One Loss: 1.0
- Jaccard Score: 1.0
- Hamming Loss Optimised: 0.1034
- Hamming Loss Threshold: 0.4079
- Zero One Loss Optimised: 0.7662
- Zero One Loss Threshold: 0.3351
- Jaccard Score Optimised: 0.7625
- Jaccard Score Threshold: 0.3149

## 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: 3.691774561796012e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2024
- 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
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Hamming Loss | Zero One Loss | Jaccard Score | Hamming Loss Optimised | Hamming Loss Threshold | Zero One Loss Optimised | Zero One Loss Threshold | Jaccard Score Optimised | Jaccard Score Threshold |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:-------------:|:-------------:|:----------------------:|:----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|
| No log        | 1.0   | 100  | 0.6553          | 0.3676       | 1.0           | 0.9280        | 0.1123                 | 0.6566                 | 0.95                    | 0.5576                  | 0.8863                  | 0.2993                  |
| No log        | 2.0   | 200  | 0.5073          | 0.1205       | 0.94          | 0.9381        | 0.1123                 | 0.6530                 | 0.8175                  | 0.4434                  | 0.7941                  | 0.4421                  |
| No log        | 3.0   | 300  | 0.4412          | 0.1121       | 0.9988        | 0.9988        | 0.1123                 | 0.5944                 | 0.7675                  | 0.3659                  | 0.7621                  | 0.3681                  |
| No log        | 4.0   | 400  | 0.4228          | 0.1123       | 1.0           | 1.0           | 0.109                  | 0.4184                 | 0.7675                  | 0.3485                  | 0.7631                  | 0.3402                  |
| 0.5269        | 5.0   | 500  | 0.4151          | 0.1123       | 1.0           | 1.0           | 0.1123                 | 0.5944                 | 0.7675                  | 0.3646                  | 0.7990                  | 0.2948                  |
| 0.5269        | 6.0   | 600  | 0.4109          | 0.1123       | 1.0           | 1.0           | 0.1051                 | 0.4182                 | 0.7662                  | 0.3532                  | 0.7631                  | 0.3362                  |
| 0.5269        | 7.0   | 700  | 0.4084          | 0.1123       | 1.0           | 1.0           | 0.1046                 | 0.4138                 | 0.7662                  | 0.3368                  | 0.7638                  | 0.3453                  |
| 0.5269        | 8.0   | 800  | 0.4059          | 0.1123       | 1.0           | 1.0           | 0.1031                 | 0.4037                 | 0.7662                  | 0.3314                  | 0.7612                  | 0.3225                  |
| 0.5269        | 9.0   | 900  | 0.4051          | 0.1123       | 1.0           | 1.0           | 0.1032                 | 0.4075                 | 0.7662                  | 0.3350                  | 0.7619                  | 0.3209                  |
| 0.4202        | 10.0  | 1000 | 0.4049          | 0.1123       | 1.0           | 1.0           | 0.1034                 | 0.4079                 | 0.7662                  | 0.3351                  | 0.7625                  | 0.3149                  |


### Framework versions

- PEFT 0.13.2
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0