---
base_model: OFA-Sys/chinese-clip-vit-base-patch16
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sentance_split_by_time_gpt_concate_2
  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/cdver57p)
# sentance_split_by_time_gpt_concate_2

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: 3.8914
- Accuracy: 0.0782

## 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: 25
- eval_batch_size: 20
- seed: 42
- gradient_accumulation_steps: 8
- 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 |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 2.0864        | 5.9928  | 1866  | 2.9935          | 0.0803   |
| 1.9035        | 11.9855 | 3732  | 3.1629          | 0.0863   |
| 1.779         | 17.9783 | 5598  | 3.2064          | 0.0870   |
| 1.7158        | 23.9711 | 7464  | 3.4417          | 0.0854   |
| 1.6832        | 29.9639 | 9330  | 3.4988          | 0.0845   |
| 1.6554        | 35.9566 | 11196 | 3.5538          | 0.0833   |
| 1.6498        | 41.9494 | 13062 | 3.6819          | 0.0819   |
| 1.6335        | 47.9422 | 14928 | 3.7696          | 0.0809   |
| 1.6339        | 53.9350 | 16794 | 3.8098          | 0.0799   |
| 1.6264        | 59.9277 | 18660 | 3.8914          | 0.0789   |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1