| | --- |
| | license: mit |
| | base_model: microsoft/deberta-v3-large |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: Classifier_with_external_sets_03 |
| | 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. --> |
| |
|
| | # Classifier_with_external_sets_03 |
| |
|
| | This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.6931 |
| | - Accuracy: 0.5034 |
| |
|
| | ## 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: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 32 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | | No log | 0.9983 | 289 | 0.6943 | 0.5034 | |
| | | 0.7019 | 2.0 | 579 | 0.6932 | 0.4966 | |
| | | 0.7019 | 2.9983 | 868 | 0.7004 | 0.5034 | |
| | | 0.6978 | 4.0 | 1158 | 0.6968 | 0.4966 | |
| | | 0.6978 | 4.9983 | 1447 | 0.6953 | 0.4966 | |
| | | 0.6961 | 6.0 | 1737 | 0.6932 | 0.5034 | |
| | | 0.6958 | 6.9983 | 2026 | 0.6932 | 0.5034 | |
| | | 0.6958 | 8.0 | 2316 | 0.6934 | 0.4966 | |
| | | 0.6942 | 8.9983 | 2605 | 0.6940 | 0.5034 | |
| | | 0.6942 | 9.9827 | 2890 | 0.6931 | 0.5034 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.40.0 |
| | - Pytorch 2.2.2+cu121 |
| | - Datasets 2.19.0 |
| | - Tokenizers 0.19.1 |
| | |
