metadata
license: mit
base_model: microsoft/deberta-v2-xxlarge
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: output1
results: []
output1
This model is a fine-tuned version of microsoft/deberta-v2-xxlarge on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7690
- Accuracy: 0.676
- Macro F1: 0.6761
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 |
|---|---|---|---|---|---|
| 1.5278 | 0.2286 | 100 | 1.1249 | 0.5146 | 0.4600 |
| 0.9452 | 0.4571 | 200 | 0.8437 | 0.645 | 0.6425 |
| 0.8367 | 0.6857 | 300 | 0.8038 | 0.6477 | 0.6531 |
| 0.8092 | 0.9143 | 400 | 0.7801 | 0.6593 | 0.6611 |
| 0.7679 | 1.1429 | 500 | 0.7868 | 0.6717 | 0.6697 |
| 0.7451 | 1.3714 | 600 | 0.7711 | 0.6647 | 0.6645 |
| 0.7467 | 1.6 | 700 | 0.7646 | 0.6659 | 0.6649 |
| 0.7261 | 1.8286 | 800 | 0.7840 | 0.6649 | 0.6632 |
| 0.7305 | 2.0571 | 900 | 0.7755 | 0.6681 | 0.6707 |
| 0.6742 | 2.2857 | 1000 | 0.7719 | 0.6691 | 0.6707 |
| 0.6728 | 2.5143 | 1100 | 0.7640 | 0.6726 | 0.6726 |
| 0.6691 | 2.7429 | 1200 | 0.7759 | 0.6761 | 0.6783 |
| 0.677 | 2.9714 | 1300 | 0.7690 | 0.676 | 0.6761 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.2
- Datasets 2.19.0
- Tokenizers 0.19.1