File size: 2,641 Bytes
67b2f21 |
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 76 77 78 79 80 |
---
license: apache-2.0
base_model: zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 10-finetuned-ausSpiders
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. -->
# 10-finetuned-ausSpiders
This model is a fine-tuned version of [zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000](https://huggingface.co/zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0399
- Accuracy: 0.9896
- Precision: 0.9831
- Recall: 0.9577
- F1: 0.9683
## 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: 0.0005
- 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.1696 | 1.0 | 767 | 0.1719 | 0.9477 | 0.9104 | 0.8399 | 0.8558 |
| 0.114 | 2.0 | 1534 | 0.0823 | 0.9754 | 0.9637 | 0.8941 | 0.9185 |
| 0.1065 | 3.0 | 2301 | 0.0857 | 0.9708 | 0.8828 | 0.8472 | 0.8572 |
| 0.112 | 4.0 | 3069 | 0.0781 | 0.9756 | 0.9361 | 0.8767 | 0.8803 |
| 0.1006 | 5.0 | 3836 | 0.0610 | 0.9821 | 0.9662 | 0.9362 | 0.9485 |
| 0.0838 | 6.0 | 4603 | 0.0571 | 0.9817 | 0.9397 | 0.9442 | 0.9380 |
| 0.0766 | 7.0 | 5370 | 0.0507 | 0.9832 | 0.9626 | 0.9175 | 0.9302 |
| 0.0523 | 8.0 | 6138 | 0.0398 | 0.9870 | 0.9470 | 0.9763 | 0.9577 |
| 0.0531 | 9.0 | 6905 | 0.0456 | 0.9892 | 0.9881 | 0.9556 | 0.9697 |
| 0.0419 | 10.0 | 7670 | 0.0399 | 0.9896 | 0.9831 | 0.9577 | 0.9683 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
|