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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: my_awesome_food_model_v2 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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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/sciarrilli/huggingface/runs/trgtu68a) |
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# my_awesome_food_model_v2 |
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This model was trained from scratch on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8053 |
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- Accuracy: 0.8083 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 512 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:| |
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| 4.4448 | 0.9932 | 110 | 4.4236 | 0.0914 | |
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| 3.8312 | 1.9955 | 221 | 3.8007 | 0.4096 | |
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| 3.1568 | 2.9977 | 332 | 3.1221 | 0.5435 | |
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| 2.4967 | 4.0 | 443 | 2.4920 | 0.6308 | |
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| 2.0432 | 4.9932 | 553 | 2.0252 | 0.6825 | |
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| 1.6512 | 5.9955 | 664 | 1.6771 | 0.7184 | |
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| 1.388 | 6.9977 | 775 | 1.4464 | 0.7367 | |
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| 1.1677 | 8.0 | 886 | 1.2782 | 0.7533 | |
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| 1.0307 | 8.9932 | 996 | 1.1741 | 0.7625 | |
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| 0.9156 | 9.9955 | 1107 | 1.0900 | 0.7741 | |
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| 0.8283 | 10.9977 | 1218 | 1.0295 | 0.7771 | |
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| 0.8078 | 12.0 | 1329 | 0.9949 | 0.7776 | |
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| 0.7643 | 12.9932 | 1439 | 0.9656 | 0.7817 | |
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| 0.6578 | 13.9955 | 1550 | 0.9274 | 0.7868 | |
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| 0.611 | 14.9977 | 1661 | 0.9051 | 0.7921 | |
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| 0.6016 | 16.0 | 1772 | 0.9009 | 0.7912 | |
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| 0.5652 | 16.9932 | 1882 | 0.8772 | 0.7963 | |
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| 0.5492 | 17.9955 | 1993 | 0.8559 | 0.7992 | |
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| 0.5054 | 18.9977 | 2104 | 0.8734 | 0.7956 | |
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| 0.5351 | 20.0 | 2215 | 0.8617 | 0.7999 | |
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| 0.4949 | 20.9932 | 2325 | 0.8487 | 0.8013 | |
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| 0.4701 | 21.9955 | 2436 | 0.8437 | 0.8013 | |
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| 0.4576 | 22.9977 | 2547 | 0.8430 | 0.8008 | |
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| 0.4573 | 24.0 | 2658 | 0.8195 | 0.8071 | |
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| 0.4399 | 24.9932 | 2768 | 0.8206 | 0.8071 | |
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| 0.424 | 25.9955 | 2879 | 0.8212 | 0.8068 | |
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| 0.4031 | 26.9977 | 2990 | 0.8202 | 0.8069 | |
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| 0.4031 | 28.0 | 3101 | 0.8173 | 0.8080 | |
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| 0.407 | 28.9932 | 3211 | 0.8051 | 0.8069 | |
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| 0.4194 | 29.7968 | 3300 | 0.8053 | 0.8083 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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