metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: deberta-base-TEST
results: []
deberta-base-TEST
This model is a fine-tuned version of microsoft/deberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3385
- Precision: 0.9472
- Recall: 0.9472
- F1: 0.9472
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| 0.3683 | 1.0 | 2500 | 0.3859 | 0.9094 | 0.9094 | 0.9094 |
| 0.2269 | 2.0 | 5000 | 0.3091 | 0.9439 | 0.9439 | 0.9439 |
| 0.1006 | 3.0 | 7500 | 0.3385 | 0.9472 | 0.9472 | 0.9472 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3