metadata
license: mit
tags:
- text-classification
- generated_from_trainer
metrics:
- f1
- precision
- recall
base_model: microsoft/deberta-v3-large
model-index:
- name: deberta-v3-large-finetuned-synthetic-translated-only
results: []
deberta-v3-large-finetuned-synthetic-translated-only
This model is a fine-tuned version of microsoft/deberta-v3-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0005
- F1: 0.9961
- Precision: 1.0
- Recall: 0.9922
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: 6e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall |
|---|---|---|---|---|---|---|
| 0.0065 | 1.0 | 10158 | 0.0022 | 0.9887 | 0.9962 | 0.9813 |
| 0.0006 | 2.0 | 20316 | 0.0030 | 0.9887 | 0.9962 | 0.9813 |
| 0.0008 | 3.0 | 30474 | 0.0029 | 0.9906 | 0.9962 | 0.9851 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1