|
--- |
|
license: apache-2.0 |
|
base_model: facebook/convnextv2-huge-22k-384 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- precision |
|
- recall |
|
- f1 |
|
model-index: |
|
- name: 5-convnextv2-huge-22k-384-finetuned-spiderTraining50-200 |
|
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. --> |
|
|
|
# 5-convnextv2-huge-22k-384-finetuned-spiderTraining50-200 |
|
|
|
This model is a fine-tuned version of [facebook/convnextv2-huge-22k-384](https://huggingface.co/facebook/convnextv2-huge-22k-384) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1990 |
|
- Accuracy: 0.9439 |
|
- Precision: 0.9439 |
|
- Recall: 0.9439 |
|
- F1: 0.9425 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 5 |
|
- eval_batch_size: 5 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 20 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
|
| 1.1014 | 1.0 | 399 | 0.5745 | 0.8428 | 0.8568 | 0.8422 | 0.8357 | |
|
| 0.5338 | 2.0 | 799 | 0.3466 | 0.8969 | 0.8995 | 0.8968 | 0.8934 | |
|
| 0.4343 | 3.0 | 1199 | 0.2666 | 0.9239 | 0.9292 | 0.9256 | 0.9231 | |
|
| 0.2723 | 4.0 | 1599 | 0.2246 | 0.9299 | 0.9332 | 0.9316 | 0.9299 | |
|
| 0.1415 | 4.99 | 1995 | 0.1990 | 0.9439 | 0.9439 | 0.9439 | 0.9425 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.33.3 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.13.3 |
|
|
