|
--- |
|
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-spiderTraining50-2000 |
|
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-spiderTraining50-2000 |
|
|
|
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: 0.2220 |
|
- Accuracy: 0.9353 |
|
- Precision: 0.9355 |
|
- Recall: 0.9353 |
|
- F1: 0.9352 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
|
| 0.7311 | 1.0 | 1250 | 0.4761 | 0.8637 | 0.8682 | 0.8637 | 0.8637 | |
|
| 0.5924 | 2.0 | 2500 | 0.3177 | 0.9084 | 0.9108 | 0.9087 | 0.9087 | |
|
| 0.4035 | 3.0 | 3750 | 0.2668 | 0.9200 | 0.9211 | 0.9202 | 0.9198 | |
|
| 0.4343 | 4.0 | 5000 | 0.2395 | 0.9290 | 0.9302 | 0.9289 | 0.9290 | |
|
| 0.381 | 5.0 | 6250 | 0.2220 | 0.9353 | 0.9355 | 0.9353 | 0.9352 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.33.3 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.13.3 |
|
|
