---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# deberta-v3-base-lora-isarcasm

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/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