metadata
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: my_model
results: []
my_model
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: 0.1746
- Accuracy: 0.9589
- F1: 0.8034
- Precision: 1.0
- Recall: 0.6714
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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 14 | 0.4759 | 0.875 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 28 | 0.3609 | 0.875 | 0.0 | 0.0 | 0.0 |
| No log | 3.0 | 42 | 0.3394 | 0.875 | 0.0 | 0.0 | 0.0 |
| No log | 4.0 | 56 | 0.3070 | 0.875 | 0.0 | 0.0 | 0.0 |
| No log | 5.0 | 70 | 0.2768 | 0.875 | 0.0 | 0.0 | 0.0 |
| No log | 6.0 | 84 | 0.2432 | 0.8893 | 0.2051 | 1.0 | 0.1143 |
| No log | 7.0 | 98 | 0.2159 | 0.9071 | 0.4091 | 1.0 | 0.2571 |
| No log | 8.0 | 112 | 0.1946 | 0.9429 | 0.7037 | 1.0 | 0.5429 |
| No log | 9.0 | 126 | 0.1798 | 0.9554 | 0.7826 | 1.0 | 0.6429 |
| No log | 10.0 | 140 | 0.1746 | 0.9589 | 0.8034 | 1.0 | 0.6714 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1