---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
model-index:
- name: bert-base-cased-finetuned-products
  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. -->

# bert-base-cased-finetuned-products

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1250

## 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: 4e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step   | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 7.1574        | 1.0   | 7595   | 6.0100          |
| 4.7853        | 2.0   | 15190  | 3.7723          |
| 3.0734        | 3.0   | 22785  | 2.7345          |
| 2.2249        | 4.0   | 30380  | 2.2894          |
| 1.746         | 5.0   | 37975  | 2.0801          |
| 1.4232        | 6.0   | 45570  | 1.9818          |
| 1.177         | 7.0   | 53165  | 1.9314          |
| 0.9785        | 8.0   | 60760  | 1.9254          |
| 0.8097        | 9.0   | 68355  | 1.9443          |
| 0.6691        | 10.0  | 75950  | 1.9722          |
| 0.5536        | 11.0  | 83545  | 2.0024          |
| 0.4616        | 12.0  | 91140  | 2.0540          |
| 0.3869        | 13.0  | 98735  | 2.0819          |
| 0.3302        | 14.0  | 106330 | 2.1114          |
| 0.2915        | 15.0  | 113925 | 2.1250          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0.post100
- Datasets 2.19.1
- Tokenizers 0.19.1