metadata
license: mit
base_model: bobbyw/deberta-v3-large_faster_learning_v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: deberta-v3-large_faster_learning_v2
results: []
deberta-v3-large_faster_learning_v2
This model is a fine-tuned version of bobbyw/deberta-v3-large_faster_learning_v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0991
- Accuracy: 0.0248
- F1: 0.0238
- Precision: 0.0122
- Recall: 0.5455
- Learning Rate: 0.0
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: 1e-06
- train_batch_size: 3
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Rate |
|---|---|---|---|---|---|---|---|---|
| 0.0174 | 1.0 | 689 | 0.1018 | 0.0238 | 0.0238 | 0.0122 | 0.5455 | 0.0008 |
| 0.019 | 2.0 | 1378 | 0.1014 | 0.0248 | 0.0258 | 0.0132 | 0.5909 | 0.0005 |
| 0.0182 | 3.0 | 2067 | 0.0979 | 0.0228 | 0.0238 | 0.0122 | 0.5455 | 0.0003 |
| 0.0171 | 4.0 | 2756 | 0.0991 | 0.0248 | 0.0238 | 0.0122 | 0.5455 | 0.0 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1