| | --- |
| | library_name: transformers |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: rlcc-new-appearance-upsample_replacement-aspect_classifier |
| | 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. --> |
| |
|
| | # rlcc-new-appearance-upsample_replacement-aspect_classifier |
| |
|
| | This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.2835 |
| | - Accuracy: 0.4477 |
| | - F1 Macro: 0.4310 |
| | - Precision Macro: 0.4551 |
| | - Recall Macro: 0.4321 |
| | - F1 Micro: 0.4477 |
| | - Precision Micro: 0.4477 |
| | - Recall Micro: 0.4477 |
| | - Total Tf: [124, 153, 401, 153] |
| |
|
| | ## 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: 2e-05 |
| | - train_batch_size: 64 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 44 |
| | - num_epochs: 20 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | F1 Micro | Precision Micro | Recall Micro | Total Tf | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------------------:| |
| | | 1.0991 | 1.0 | 45 | 1.0927 | 0.4043 | 0.2892 | 0.2570 | 0.3606 | 0.4043 | 0.4043 | 0.4043 | [112, 165, 389, 165] | |
| | | 1.0885 | 2.0 | 90 | 1.0899 | 0.4224 | 0.3296 | 0.2843 | 0.3939 | 0.4224 | 0.4224 | 0.4224 | [117, 160, 394, 160] | |
| | | 1.0124 | 3.0 | 135 | 1.1232 | 0.3755 | 0.3630 | 0.3653 | 0.3640 | 0.3755 | 0.3755 | 0.3755 | [104, 173, 381, 173] | |
| | | 0.7841 | 4.0 | 180 | 1.1267 | 0.4440 | 0.4437 | 0.4497 | 0.4535 | 0.4440 | 0.4440 | 0.4440 | [123, 154, 400, 154] | |
| | | 0.6049 | 5.0 | 225 | 1.2197 | 0.4296 | 0.4147 | 0.4294 | 0.4161 | 0.4296 | 0.4296 | 0.4296 | [119, 158, 396, 158] | |
| | | 0.4992 | 6.0 | 270 | 1.2835 | 0.4477 | 0.4310 | 0.4551 | 0.4321 | 0.4477 | 0.4477 | 0.4477 | [124, 153, 401, 153] | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.52.4 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.6.0 |
| | - Tokenizers 0.21.2 |
| | |
