metadata
license: apache-2.0
base_model: hallisky/sarcasm-classifier-gpt4-data
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: taskA-hallisky-sarcasm-classifier-gpt4-data
results: []
taskA-hallisky-sarcasm-classifier-gpt4-data
This model is a fine-tuned version of hallisky/sarcasm-classifier-gpt4-data on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9103
- Accuracy: 0.7722
- Precision: 0.5525
- Recall: 0.4697
- F1: 0.5078
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: 4e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.5499 | 0.7752 | 500 | 0.6671 | 0.7599 | 0.5307 | 0.3487 | 0.4209 |
| 0.4267 | 1.5504 | 1000 | 0.6445 | 0.7664 | 0.5441 | 0.4092 | 0.4671 |
| 0.3895 | 2.3256 | 1500 | 0.7337 | 0.7851 | 0.6522 | 0.3026 | 0.4134 |
| 0.3492 | 3.1008 | 2000 | 0.6803 | 0.7823 | 0.5830 | 0.4553 | 0.5113 |
| 0.3251 | 3.8760 | 2500 | 0.7877 | 0.7621 | 0.5251 | 0.5130 | 0.5190 |
| 0.308 | 4.6512 | 3000 | 0.9103 | 0.7722 | 0.5525 | 0.4697 | 0.5078 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1