Model save

README.md

@@ -1,83 +0,0 @@
----
-license: apache-2.0
-tags:
-- generated_from_trainer
-datasets:
-- imagefolder
-metrics:
-- accuracy
-model-index:
-- name: swinv2-tiny-patch4-window8-256-finetuned-thai
-  results:
-  - task:
-      name: Image Classification
-      type: image-classification
-    dataset:
-      name: imagefolder
-      type: imagefolder
-      config: default
-      split: val
-      args: default
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.87375
----
-
-<!-- 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. -->
-
-# swinv2-tiny-patch4-window8-256-finetuned-thai
-
-This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.4391
-- Accuracy: 0.8738
-
-## 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: 64
-- eval_batch_size: 64
-- seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 256
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 7
-
-### Training results
-
-| Training Loss | Epoch | Step | Accuracy | Validation Loss |
-|:-------------:|:-----:|:----:|:--------:|:---------------:|
-| 2.6781        | 0.99  | 47   | 0.5475   | 1.8040          |
-| 1.3191        | 1.99  | 94   | 0.745    | 0.9501          |
-| 1.078         | 2.98  | 141  | 0.7969   | 0.7767          |
-| 0.9125        | 3.99  | 188  | 0.6060   | 0.8406          |
-| 0.7527        | 4.99  | 235  | 0.5214   | 0.8575          |
-| 0.6852        | 5.98  | 282  | 0.4588   | 0.8656          |
-| 0.6233        | 6.98  | 329  | 0.4391   | 0.8738          |
-
-
-### Framework versions
-
-- Transformers 4.28.1
-- Pytorch 2.0.0+cu118
-- Datasets 2.11.0
-- Tokenizers 0.13.3