---
library_name: transformers
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Final_ManufacturedObjects_STL_model
  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. -->

# Final_ManufacturedObjects_STL_model

This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1199
- Precision: 0.9873
- Recall: 0.9852
- F1: 0.9863
- Accuracy: 0.9825

## 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: 2e-05
- 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: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1069        | 1.0   | 523  | 0.0714          | 0.9823    | 0.9791 | 0.9807 | 0.9758   |
| 0.0411        | 2.0   | 1046 | 0.0689          | 0.9873    | 0.9827 | 0.9850 | 0.9810   |
| 0.0221        | 3.0   | 1569 | 0.0726          | 0.9864    | 0.9845 | 0.9854 | 0.9812   |
| 0.0132        | 4.0   | 2092 | 0.0867          | 0.9870    | 0.9856 | 0.9863 | 0.9820   |
| 0.0081        | 5.0   | 2615 | 0.0973          | 0.9868    | 0.9853 | 0.9861 | 0.9820   |
| 0.0042        | 6.0   | 3138 | 0.1079          | 0.9875    | 0.9852 | 0.9863 | 0.9823   |
| 0.0031        | 7.0   | 3661 | 0.1179          | 0.9881    | 0.9856 | 0.9868 | 0.9825   |
| 0.0016        | 8.0   | 4184 | 0.1146          | 0.9881    | 0.9859 | 0.9870 | 0.9833   |
| 0.0013        | 9.0   | 4707 | 0.1190          | 0.9879    | 0.9856 | 0.9867 | 0.9831   |
| 0.0009        | 10.0  | 5230 | 0.1199          | 0.9873    | 0.9852 | 0.9863 | 0.9825   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0