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---
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-25-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-25-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: 0.1655
- Accuracy: 0.9421

## 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: 25

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7994        | 1.0   | 1062  | 0.7879          | 0.8243   |
| 0.5403        | 2.0   | 2124  | 0.5089          | 0.8545   |
| 0.4235        | 3.0   | 3186  | 0.3855          | 0.8819   |
| 0.3556        | 4.0   | 4248  | 0.4072          | 0.8656   |
| 0.3133        | 5.0   | 5310  | 0.3077          | 0.8999   |
| 0.2998        | 6.0   | 6372  | 0.3031          | 0.9025   |
| 0.2842        | 7.0   | 7434  | 0.2610          | 0.9100   |
| 0.2773        | 8.0   | 8496  | 0.2443          | 0.9157   |
| 0.2413        | 9.0   | 9558  | 0.2339          | 0.9204   |
| 0.2394        | 10.0  | 10620 | 0.2241          | 0.9223   |
| 0.2305        | 11.0  | 11682 | 0.2230          | 0.9195   |
| 0.2119        | 12.0  | 12744 | 0.2129          | 0.9273   |
| 0.2106        | 13.0  | 13806 | 0.2186          | 0.9228   |
| 0.1973        | 14.0  | 14868 | 0.1961          | 0.9319   |
| 0.1993        | 15.0  | 15930 | 0.1903          | 0.9337   |
| 0.1863        | 16.0  | 16992 | 0.1888          | 0.9322   |
| 0.1883        | 17.0  | 18054 | 0.1966          | 0.9288   |
| 0.1879        | 18.0  | 19116 | 0.1794          | 0.9380   |
| 0.1856        | 19.0  | 20178 | 0.1786          | 0.9366   |
| 0.1808        | 20.0  | 21240 | 0.1838          | 0.9344   |
| 0.1711        | 21.0  | 22302 | 0.1749          | 0.9383   |
| 0.1689        | 22.0  | 23364 | 0.1694          | 0.9405   |
| 0.17          | 23.0  | 24426 | 0.1687          | 0.9411   |
| 0.1648        | 24.0  | 25488 | 0.1684          | 0.9403   |
| 0.1665        | 25.0  | 26550 | 0.1655          | 0.9421   |


### Framework versions

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