metadata
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-xsmall
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: deberta-v3-xsmall-Label_B-1024-Epochs-2
results: []
deberta-v3-xsmall-Label_B-1024-epoch-2
This model is a fine-tuned version of microsoft/deberta-v3-xsmall on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0823
- Accuracy: 0.9779
- F1: 0.9780
- Precision: 0.9786
- Recall: 0.9779
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: 10
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.1048 | 0.9994 | 1279 | 0.1988 | 0.9411 | 0.9408 | 0.9499 | 0.9411 |
| 0.0125 | 1.9988 | 2558 | 0.0823 | 0.9779 | 0.9780 | 0.9786 | 0.9779 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0