File size: 2,096 Bytes
5bec1bf 492c08e 5bec1bf 492c08e 5bec1bf 492c08e 5bec1bf 492c08e 5bec1bf 492c08e 5bec1bf 492c08e 5bec1bf 492c08e 5bec1bf 492c08e 5bec1bf 492c08e 5bec1bf 492c08e 5bec1bf 492c08e 5bec1bf 492c08e 5bec1bf 492c08e 5bec1bf 492c08e 5bec1bf 492c08e 5bec1bf 492c08e 5bec1bf 492c08e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 |
---
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: []
---
<!-- 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. -->
# taskA-hallisky-sarcasm-classifier-gpt4-data
This model is a fine-tuned version of [hallisky/sarcasm-classifier-gpt4-data](https://huggingface.co/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
|