metadata
library_name: transformers
base_model: OFA-Sys/chinese-clip-vit-base-patch16
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fusion_None_sep_SEP_describe_llama
results: []
fusion_None_sep_SEP_describe_llama
This model is a fine-tuned version of OFA-Sys/chinese-clip-vit-base-patch16 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.5783
- Accuracy: 0.2842
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: 60
- eval_batch_size: 20
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 480
- 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 |
|---|---|---|---|---|
| 2.686 | 5.9653 | 774 | 2.3316 | 0.3232 |
| 2.5095 | 11.9306 | 1548 | 2.3506 | 0.3168 |
| 2.4304 | 17.8960 | 2322 | 2.4180 | 0.3103 |
| 2.3871 | 23.8613 | 3096 | 2.4723 | 0.3052 |
| 2.3556 | 29.8266 | 3870 | 2.5127 | 0.3 |
| 2.3325 | 35.7919 | 4644 | 2.5233 | 0.2965 |
| 2.3155 | 41.7572 | 5418 | 2.5572 | 0.2930 |
| 2.3137 | 47.7225 | 6192 | 2.5639 | 0.2903 |
| 2.2978 | 53.6879 | 6966 | 2.5749 | 0.2878 |
| 2.2964 | 59.6532 | 7740 | 2.5783 | 0.2858 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.20.0