metadata
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: hr_techgroup
results: []
hr_techgroup
This model is a fine-tuned version of microsoft/deberta-v3-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0512
- Accuracy: 0.9773
- F1: 0.9784
- Precision: 0.9790
- Recall: 0.9779
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: 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 | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 114 | 0.0839 | 0.9618 | 0.9624 | 0.9624 | 0.9624 |
| No log | 2.0 | 228 | 0.0536 | 0.9740 | 0.9749 | 0.9746 | 0.9751 |
| No log | 3.0 | 342 | 0.0523 | 0.9751 | 0.9757 | 0.9762 | 0.9751 |
| No log | 4.0 | 456 | 0.0517 | 0.9768 | 0.9776 | 0.9773 | 0.9779 |
| 0.1003 | 5.0 | 570 | 0.0512 | 0.9773 | 0.9784 | 0.9790 | 0.9779 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1