metadata
license: mit
base_model: bobbyw/deberta-v3-large_v1_no_entities_with_context
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: deberta-v3-large_v1_no_entities_with_context
results: []
deberta-v3-large_v1_no_entities_with_context
This model is a fine-tuned version of bobbyw/deberta-v3-large_v1_no_entities_with_context on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0259
- Accuracy: 0.0045
- F1: 0.0090
- Precision: 0.0045
- Recall: 1.0
- 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: 0.0002
- 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 |
|---|---|---|---|---|---|---|---|---|
| 0.0312 | 1.0 | 540 | 0.0264 | 0.0045 | 0.0090 | 0.0045 | 1.0 | 0.0002 |
| 0.0302 | 2.0 | 1080 | 0.0266 | 0.0045 | 0.0090 | 0.0045 | 1.0 | 0.0001 |
| 0.0315 | 3.0 | 1620 | 0.0259 | 0.0045 | 0.0090 | 0.0045 | 1.0 | 5e-05 |
| 0.03 | 4.0 | 2160 | 0.0259 | 0.0045 | 0.0090 | 0.0045 | 1.0 | 0.0 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1