| --- |
| license: apache-2.0 |
| base_model: raffel-22/emotion_classification_2 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: emotion_classification_2_continue |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: train |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.725 |
| --- |
| |
| <!-- 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. --> |
|
|
| # emotion_classification_2_continue |
| |
| This model is a fine-tuned version of [raffel-22/emotion_classification_2](https://huggingface.co/raffel-22/emotion_classification_2) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8978 |
| - Accuracy: 0.725 |
| |
| ## 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: 4e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 30 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 20 | 0.9714 | 0.7063 | |
| | No log | 2.0 | 40 | 0.9432 | 0.7188 | |
| | No log | 3.0 | 60 | 0.9633 | 0.7 | |
| | No log | 4.0 | 80 | 0.9322 | 0.7375 | |
| | No log | 5.0 | 100 | 0.8530 | 0.7063 | |
| | No log | 6.0 | 120 | 0.9063 | 0.7063 | |
| | No log | 7.0 | 140 | 0.8451 | 0.7125 | |
| | No log | 8.0 | 160 | 0.9672 | 0.6375 | |
| | No log | 9.0 | 180 | 0.9036 | 0.6937 | |
| | No log | 10.0 | 200 | 0.9261 | 0.6562 | |
| | No log | 11.0 | 220 | 0.8963 | 0.6937 | |
| | No log | 12.0 | 240 | 0.8852 | 0.7188 | |
| | No log | 13.0 | 260 | 0.8728 | 0.7063 | |
| | No log | 14.0 | 280 | 0.9559 | 0.6875 | |
| | No log | 15.0 | 300 | 0.9352 | 0.65 | |
| | No log | 16.0 | 320 | 0.8638 | 0.7 | |
| | No log | 17.0 | 340 | 0.9156 | 0.7 | |
| | No log | 18.0 | 360 | 1.0299 | 0.6687 | |
| | No log | 19.0 | 380 | 0.8983 | 0.675 | |
| | No log | 20.0 | 400 | 0.8858 | 0.7063 | |
| | No log | 21.0 | 420 | 0.9699 | 0.6937 | |
| | No log | 22.0 | 440 | 1.0603 | 0.625 | |
| | No log | 23.0 | 460 | 1.0404 | 0.6312 | |
| | No log | 24.0 | 480 | 0.8838 | 0.6937 | |
| | 0.4269 | 25.0 | 500 | 0.9280 | 0.6937 | |
| | 0.4269 | 26.0 | 520 | 0.9456 | 0.6937 | |
| | 0.4269 | 27.0 | 540 | 0.9640 | 0.6937 | |
| | 0.4269 | 28.0 | 560 | 0.9865 | 0.6937 | |
| | 0.4269 | 29.0 | 580 | 0.8900 | 0.7188 | |
| | 0.4269 | 30.0 | 600 | 0.9408 | 0.7063 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.33.2 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.5 |
| - Tokenizers 0.13.3 |
| |
