File size: 2,151 Bytes
ed6ff1a |
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-384-0.0001-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. -->
# convnextv2-tiny-22k-384-0.0001-finetuned-spiderTraining50-200
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: 0.4409
- Accuracy: 0.8729
- Precision: 0.8706
- Recall: 0.8714
- F1: 0.8672
## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.6172 | 1.0 | 125 | 1.2793 | 0.6767 | 0.7024 | 0.6713 | 0.6581 |
| 0.9187 | 2.0 | 250 | 0.7649 | 0.7918 | 0.8129 | 0.7878 | 0.7869 |
| 0.6421 | 3.0 | 375 | 0.5605 | 0.8458 | 0.8577 | 0.8418 | 0.8397 |
| 0.5017 | 4.0 | 500 | 0.4645 | 0.8719 | 0.8717 | 0.8722 | 0.8672 |
| 0.4235 | 5.0 | 625 | 0.4409 | 0.8729 | 0.8706 | 0.8714 | 0.8672 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
|