williamdeli
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End of training
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README.md
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---
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tags:
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- generated_from_trainer
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datasets:
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- imagefolder
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metrics:
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- accuracy
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model-index:
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- name: emotion-classification
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results:
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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: imagefolder
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type: imagefolder
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config: default
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split: train
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.875
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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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# emotion-classification
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This model was trained from scratch on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8208
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- Accuracy: 0.875
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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: 3e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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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: 3
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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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| 0.8456 | 1.0 | 5 | 0.8537 | 0.8562 |
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| 0.7982 | 2.0 | 10 | 0.8021 | 0.8875 |
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| 0.8028 | 3.0 | 15 | 0.8028 | 0.8438 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.4.0
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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model.safetensors
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runs/Sep02_23-43-18_William/events.out.tfevents.1725296349.William.18064.1
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size 405
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