File size: 2,383 Bytes
8125b60 cbb8197 8125b60 |
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 |
---
base_model: OFA-Sys/chinese-clip-vit-base-patch16
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: aoi_clip_high_resolution_concate_fusin_crop_each_text
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/shark_meow_team/huggingface/runs/5lcdjsus)
# aoi_clip_high_resolution_concate_fusin_crop_each_text
This model is a fine-tuned version of [OFA-Sys/chinese-clip-vit-base-patch16](https://huggingface.co/OFA-Sys/chinese-clip-vit-base-patch16) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4957
- Accuracy: 0.0648
## 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: 1e-05
- train_batch_size: 20
- eval_batch_size: 20
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 200
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 1.7286 | 5.9821 | 1602 | 3.0151 | 0.0654 |
| 1.6207 | 11.9642 | 3204 | 3.2376 | 0.0665 |
| 1.5399 | 17.9462 | 4806 | 3.2386 | 0.0685 |
| 1.4981 | 23.9283 | 6408 | 3.3545 | 0.0673 |
| 1.4774 | 29.9104 | 8010 | 3.3404 | 0.0677 |
| 1.4648 | 35.8925 | 9612 | 3.4236 | 0.0670 |
| 1.4549 | 41.8745 | 11214 | 3.4689 | 0.0664 |
| 1.4528 | 47.8566 | 12816 | 3.5205 | 0.0659 |
| 1.4538 | 53.8387 | 14418 | 3.4703 | 0.0655 |
| 1.4519 | 59.8208 | 16020 | 3.4957 | 0.0651 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|