metadata
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: mdeberta-v3-base-azsci-topics
results: []
mdeberta-v3-base-azsci-topics
This model is a fine-tuned version of microsoft/mdeberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5213
- Precision: 0.8633
- Recall: 0.8759
- F1: 0.8685
- Accuracy: 0.8759
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: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 288 | 0.9919 | 0.6713 | 0.7465 | 0.6959 | 0.7465 |
| 1.4813 | 2.0 | 576 | 0.7035 | 0.7994 | 0.8238 | 0.8022 | 0.8238 |
| 1.4813 | 3.0 | 864 | 0.5605 | 0.8540 | 0.8568 | 0.8462 | 0.8568 |
| 0.5512 | 4.0 | 1152 | 0.5296 | 0.8615 | 0.8689 | 0.8623 | 0.8689 |
| 0.5512 | 5.0 | 1440 | 0.5213 | 0.8633 | 0.8759 | 0.8685 | 0.8759 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2