metadata

library_name: transformers
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: defect-classification-llama-baseline-25-epochs
    results: []

defect-classification-llama-baseline-25-epochs

This model is a fine-tuned version of 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