metadata
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: deberta-v3-base-lora-isarcasm
results: []
deberta-v3-base-lora-isarcasm
This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6943
- Accuracy: 0.1770
- F1: 0.3008
- Precision: 0.1770
- Recall: 1.0
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: 0.005
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 54 | 0.7069 | 0.8286 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 108 | 0.6931 | 0.8286 | 0.0 | 0.0 | 0.0 |
| No log | 3.0 | 162 | 0.6986 | 0.8286 | 0.0 | 0.0 | 0.0 |
| No log | 4.0 | 216 | 0.6946 | 0.1714 | 0.2927 | 0.1714 | 1.0 |
| No log | 5.0 | 270 | 0.6939 | 0.1714 | 0.2927 | 0.1714 | 1.0 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3