metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: group4_non_all_zero
results: []
group4_non_all_zero
This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2820
- Precision: 0.0006
- Recall: 0.08
- F1: 0.0012
- Accuracy: 0.4380
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 5 | 2.1670 | 0.0 | 0.0 | 0.0 | 0.0084 |
| No log | 2.0 | 10 | 2.3289 | 0.0 | 0.0 | 0.0 | 0.0078 |
| No log | 3.0 | 15 | 2.3316 | 0.0 | 0.0 | 0.0 | 0.0078 |
| No log | 4.0 | 20 | 2.0441 | 0.0 | 0.0 | 0.0 | 0.0078 |
| No log | 5.0 | 25 | 2.4322 | 0.0 | 0.0 | 0.0 | 0.0078 |
| No log | 6.0 | 30 | 1.7898 | 0.0 | 0.0 | 0.0 | 0.0106 |
| No log | 7.0 | 35 | 1.8590 | 0.0002 | 0.0133 | 0.0004 | 0.0104 |
| No log | 8.0 | 40 | 1.7022 | 0.0002 | 0.0133 | 0.0004 | 0.0250 |
| No log | 9.0 | 45 | 1.5775 | 0.0004 | 0.04 | 0.0007 | 0.1004 |
| No log | 10.0 | 50 | 1.4837 | 0.0006 | 0.08 | 0.0011 | 0.1939 |
| No log | 11.0 | 55 | 1.3180 | 0.0004 | 0.0533 | 0.0008 | 0.3309 |
| No log | 12.0 | 60 | 1.3418 | 0.0005 | 0.0667 | 0.0011 | 0.3799 |
| No log | 13.0 | 65 | 1.3140 | 0.0005 | 0.0667 | 0.0010 | 0.4117 |
| No log | 14.0 | 70 | 1.3444 | 0.0004 | 0.0533 | 0.0008 | 0.4048 |
| No log | 15.0 | 75 | 1.2820 | 0.0006 | 0.08 | 0.0012 | 0.4380 |
Framework versions
- Transformers 4.30.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.13.3