---
library_name: transformers
license: llama3.2
base_model: meta-llama/Llama-3.2-1B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: defect-classification-llama-baseline-10-epochs
  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. -->

# defect-classification-llama-baseline-10-epochs

This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2633
- Accuracy: 0.9165

## 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: 512
- eval_batch_size: 512
- seed: 42
- optimizer: Use 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 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8939        | 1.0   | 1062  | 0.8390          | 0.8097   |
| 0.5659        | 2.0   | 2124  | 0.5772          | 0.8416   |
| 0.4494        | 3.0   | 3186  | 0.5062          | 0.8610   |
| 0.3925        | 4.0   | 4248  | 0.4691          | 0.8758   |
| 0.3508        | 5.0   | 5310  | 0.3363          | 0.8998   |
| 0.3107        | 6.0   | 6372  | 0.3099          | 0.9026   |
| 0.2938        | 7.0   | 7434  | 0.2935          | 0.9087   |
| 0.2864        | 8.0   | 8496  | 0.2787          | 0.9124   |
| 0.2675        | 9.0   | 9558  | 0.2777          | 0.9105   |
| 0.2673        | 10.0  | 10620 | 0.2633          | 0.9165   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0