metadata
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: my_awesome_model
results: []
my_awesome_model
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: 0.4386
- Accuracy: 0.8569
- Precision: 0.8576
- Recall: 0.8571
- F1: 0.8559
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: 16
- eval_batch_size: 16
- 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 | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.5211 | 1.0 | 5000 | 0.5037 | 0.8327 | 0.8408 | 0.8331 | 0.8294 |
| 0.4159 | 2.0 | 10000 | 0.4410 | 0.8517 | 0.8546 | 0.8520 | 0.8519 |
| 0.3468 | 3.0 | 15000 | 0.4386 | 0.8569 | 0.8576 | 0.8571 | 0.8559 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1