| | --- |
| | license: apache-2.0 |
| | tags: |
| | - image-classification |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: Train |
| | 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. --> |
| |
|
| | # Train |
| |
|
| | This model is a fine-tuned version of [microsoft/resnet-101](https://huggingface.co/microsoft/resnet-101) on the TrashBox dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.7726 |
| | - Accuracy: 0.4374 |
| |
|
| | ## 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: 0.0002 |
| | - train_batch_size: 2 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 2 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 3.1529 | 0.13 | 100 | 3.2116 | 0.0590 | |
| | | 3.1644 | 0.26 | 200 | 3.2096 | 0.0692 | |
| | | 3.1549 | 0.39 | 300 | 3.1986 | 0.0692 | |
| | | 3.2998 | 0.51 | 400 | 3.1968 | 0.1077 | |
| | | 3.1344 | 0.64 | 500 | 3.1667 | 0.1718 | |
| | | 3.3638 | 0.77 | 600 | 3.1384 | 0.1744 | |
| | | 3.1482 | 0.9 | 700 | 3.0966 | 0.2026 | |
| | | 3.1366 | 1.03 | 800 | 3.0484 | 0.1897 | |
| | | 3.0206 | 1.16 | 900 | 3.0164 | 0.3026 | |
| | | 2.921 | 1.29 | 1000 | 2.9846 | 0.3231 | |
| | | 3.0027 | 1.41 | 1100 | 2.9338 | 0.3359 | |
| | | 2.9047 | 1.54 | 1200 | 2.8917 | 0.3462 | |
| | | 2.8579 | 1.67 | 1300 | 2.8616 | 0.4026 | |
| | | 2.988 | 1.8 | 1400 | 2.7832 | 0.4077 | |
| | | 2.8553 | 1.93 | 1500 | 2.8217 | 0.3872 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.30.1 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.12.0 |
| | - Tokenizers 0.13.3 |
| |
|
