| | --- |
| | license: mit |
| | base_model: microsoft/deberta-v3-small |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - precision |
| | - recall |
| | model-index: |
| | - name: fin_techgroup |
| | 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. --> |
| |
|
| | # fin_techgroup |
| | |
| | This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0571 |
| | - Accuracy: 0.9765 |
| | - F1: 0.9765 |
| | - Precision: 0.9765 |
| | - Recall: 0.9765 |
| | |
| | ## 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: 128 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 8 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | | No log | 1.0 | 64 | 0.1279 | 0.9314 | 0.9345 | 0.9318 | 0.9373 | |
| | | No log | 2.0 | 128 | 0.0711 | 0.9667 | 0.9667 | 0.9667 | 0.9667 | |
| | | No log | 3.0 | 192 | 0.0786 | 0.9618 | 0.9628 | 0.9618 | 0.9637 | |
| | | No log | 4.0 | 256 | 0.0513 | 0.9775 | 0.9775 | 0.9775 | 0.9775 | |
| | | No log | 5.0 | 320 | 0.0616 | 0.9716 | 0.9721 | 0.9716 | 0.9725 | |
| | | No log | 6.0 | 384 | 0.0596 | 0.9765 | 0.9765 | 0.9765 | 0.9765 | |
| | | No log | 7.0 | 448 | 0.0612 | 0.9765 | 0.9765 | 0.9765 | 0.9765 | |
| | | 0.0727 | 8.0 | 512 | 0.0571 | 0.9765 | 0.9765 | 0.9765 | 0.9765 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.42.4 |
| | - Pytorch 2.3.1+cu121 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| | |
