metadata
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: ops_subcate
results: []
ops_subcate
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: 0.1575
- Accuracy: 0.7428
- F1: 0.7647
- Precision: 0.7715
- Recall: 0.7581
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: 64
- eval_batch_size: 128
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 49 | 0.1300 | 0.7291 | 0.7604 | 0.7883 | 0.7345 |
| No log | 2.0 | 98 | 0.1272 | 0.7391 | 0.7707 | 0.7989 | 0.7444 |
| No log | 3.0 | 147 | 0.1294 | 0.7391 | 0.7654 | 0.7918 | 0.7407 |
| No log | 4.0 | 196 | 0.1388 | 0.7341 | 0.7567 | 0.7733 | 0.7407 |
| No log | 5.0 | 245 | 0.1326 | 0.7541 | 0.7791 | 0.8026 | 0.7568 |
| No log | 6.0 | 294 | 0.1407 | 0.7478 | 0.7743 | 0.7940 | 0.7556 |
| No log | 7.0 | 343 | 0.1445 | 0.7341 | 0.7576 | 0.7712 | 0.7444 |
| No log | 8.0 | 392 | 0.1533 | 0.7528 | 0.7684 | 0.7776 | 0.7593 |
| No log | 9.0 | 441 | 0.1573 | 0.7628 | 0.7747 | 0.7816 | 0.7680 |
| No log | 10.0 | 490 | 0.1575 | 0.7428 | 0.7647 | 0.7715 | 0.7581 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1