File size: 2,132 Bytes
cfaa8bf 8b8c690 cfaa8bf 8b8c690 cfaa8bf 8b8c690 cfaa8bf 8b8c690 cfaa8bf |
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 73 74 75 |
---
license: apache-2.0
base_model: facebook/convnextv2-tiny-22k-384
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: convnextv2-tiny-22k-384-finetuned-spiderTraining5-100
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. -->
# convnextv2-tiny-22k-384-finetuned-spiderTraining5-100
This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-384](https://huggingface.co/facebook/convnextv2-tiny-22k-384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7208
- Accuracy: 0.88
- Precision: 0.8822
- Recall: 0.8936
- F1: 0.8805
## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log | 0.96 | 6 | 1.3602 | 0.52 | 0.5198 | 0.5390 | 0.5169 |
| 1.4377 | 1.92 | 12 | 1.0444 | 0.78 | 0.7903 | 0.7869 | 0.7804 |
| 1.4377 | 2.88 | 18 | 0.8560 | 0.86 | 0.8636 | 0.8736 | 0.8598 |
| 0.9338 | 4.0 | 25 | 0.7443 | 0.86 | 0.8636 | 0.8736 | 0.8598 |
| 0.7051 | 4.8 | 30 | 0.7208 | 0.88 | 0.8822 | 0.8936 | 0.8805 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
|