---
base_model: vikp/line_detector_3
tags:
- generated_from_trainer
model-index:
- name: line_detector_3
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/vikp/line_detector/runs/5crpjf7u)
# line_detector_3

This model is a fine-tuned version of [vikp/line_detector_3](https://huggingface.co/vikp/line_detector_3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1230

## 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: 6e-05
- train_batch_size: 20
- eval_batch_size: 12
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 80
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.1302        | 0.1527 | 1000  | 0.1327          |
| 0.1147        | 0.3054 | 2000  | 0.1314          |
| 0.1395        | 0.4581 | 3000  | 0.1318          |
| 0.1302        | 0.6108 | 4000  | 0.1312          |
| 0.1349        | 0.7635 | 5000  | 0.1315          |
| 0.1431        | 0.9162 | 6000  | 0.1305          |
| 0.1318        | 1.0689 | 7000  | 0.1305          |
| 0.118         | 1.2216 | 8000  | 0.1295          |
| 0.1116        | 1.3743 | 9000  | 0.1286          |
| 0.1513        | 1.5270 | 10000 | 0.1273          |
| 0.1158        | 1.6796 | 11000 | 0.1290          |
| 0.1408        | 1.8323 | 12000 | 0.1289          |
| 0.1227        | 1.9850 | 13000 | 0.1281          |
| 0.1347        | 2.1377 | 14000 | 0.1291          |
| 0.1066        | 2.2904 | 15000 | 0.1285          |
| 0.116         | 2.4431 | 16000 | 0.1275          |
| 0.1164        | 2.5958 | 17000 | 0.1253          |
| 0.1269        | 2.7485 | 18000 | 0.1259          |
| 0.1293        | 2.9012 | 19000 | 0.1256          |
| 0.1241        | 3.0539 | 20000 | 0.1245          |
| 0.1329        | 3.2066 | 21000 | 0.1263          |
| 0.1166        | 3.3593 | 22000 | 0.1266          |
| 0.1292        | 3.5120 | 23000 | 0.1230          |
| 0.1189        | 3.6647 | 24000 | 0.1274          |
| 0.1073        | 3.8174 | 25000 | 0.1251          |
| 0.1308        | 3.9701 | 26000 | 0.1230          |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1