Visualize in Weights & Biases Visualize in Weights & Biases Visualize in Weights & Biases Visualize in Weights & Biases

xclip-base-patch32-finetuned-custom-subset

This model is a fine-tuned version of microsoft/xclip-base-patch32 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5862
  • Accuracy: 0.7308

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 1420

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.8431 0.0507 72 0.5928 0.7308
0.6657 1.0507 144 0.7383 0.7308
0.8019 2.0507 216 0.6047 0.7308
0.6275 3.0507 288 0.5946 0.7308
0.561 4.0507 360 0.6646 0.7308
0.594 5.0507 432 0.6098 0.7308
0.6472 6.0507 504 0.5915 0.7308
0.623 7.0507 576 0.5948 0.7308
0.5711 8.0507 648 0.6056 0.7308
0.5967 9.0507 720 0.5887 0.7308
0.5831 10.0507 792 0.5860 0.7308
0.6101 11.0507 864 0.6044 0.7308
0.6265 12.0507 936 0.5856 0.7308
0.6373 13.0507 1008 0.5882 0.7308
0.665 14.0507 1080 0.5852 0.7308
0.6183 15.0507 1152 0.5837 0.7308
0.7786 16.0507 1224 0.5834 0.7308
0.5489 17.0507 1296 0.5849 0.7308
0.6512 18.0507 1368 0.5843 0.7308
0.5266 19.0366 1420 0.5862 0.7308

Framework versions

  • Transformers 4.42.0.dev0
  • Pytorch 2.1.1
  • Datasets 2.13.2
  • Tokenizers 0.19.1
Downloads last month
23
Safetensors
Model size
86.2M params
Tensor type
F32
·
Inference API
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for peter881122/xclip-base-patch32-finetuned-custom-subset

Finetuned
(2)
this model