metadata
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: kaggle-math
results: []
kaggle-math
This model is a fine-tuned version of microsoft/deberta-v3-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6024
- Accuracy: 0.8204
- F1: 0.8204
- Precision: 0.8204
- Recall: 0.8204
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: 5e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.6125 | 1.0 | 680 | 0.8193 | 0.7782 | 0.7782 | 0.7782 | 0.7782 |
| 0.5557 | 2.0 | 1360 | 0.6190 | 0.7998 | 0.7998 | 0.7998 | 0.7998 |
| 0.4949 | 3.0 | 2040 | 0.6024 | 0.8204 | 0.8204 | 0.8204 | 0.8204 |
Framework versions
- Transformers 4.38.0
- Pytorch 2.5.1+cu118
- Datasets 3.2.0
- Tokenizers 0.15.2