End of training

README.md

@@ -16,13 +16,13 @@ model-index:
     dataset:
       name: imagefolder
       type: imagefolder
-      config: default
-      split: train[:800]
-      args: default
+      config: FastJobs--Visual_Emotional_Analysis
+      split: train[:-1]
+      args: FastJobs--Visual_Emotional_Analysis
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.45625
+      value: 0.5625
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.4306
-- Accuracy: 0.4562
+- Loss: 1.6256
+- Accuracy: 0.5625
 
 ## Model description
 
@@ -52,7 +52,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.00012
+- learning_rate: 0.00025
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
@@ -61,22 +61,32 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 5
+- num_epochs: 15
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.8907        | 1.0   | 10   | 1.8303          | 0.3438   |
-| 1.6499        | 2.0   | 20   | 1.6015          | 0.4062   |
-| 1.4595        | 3.0   | 30   | 1.5066          | 0.45     |
-| 1.3577        | 4.0   | 40   | 1.4472          | 0.4562   |
-| 1.2785        | 5.0   | 50   | 1.4245          | 0.4813   |
+| No log        | 1.0   | 10   | 1.7794          | 0.4875   |
+| No log        | 2.0   | 20   | 1.6813          | 0.4938   |
+| 0.2276        | 3.0   | 30   | 1.7602          | 0.4875   |
+| 0.2276        | 4.0   | 40   | 1.9172          | 0.4562   |
+| 0.2048        | 5.0   | 50   | 1.9316          | 0.4625   |
+| 0.2048        | 6.0   | 60   | 1.8285          | 0.5      |
+| 0.2048        | 7.0   | 70   | 1.6341          | 0.5687   |
+| 0.1617        | 8.0   | 80   | 1.7461          | 0.5375   |
+| 0.1617        | 9.0   | 90   | 1.6544          | 0.5312   |
+| 0.1766        | 10.0  | 100  | 1.9449          | 0.4875   |
+| 0.1766        | 11.0  | 110  | 1.7565          | 0.5125   |
+| 0.1766        | 12.0  | 120  | 1.8936          | 0.5      |
+| 0.1979        | 13.0  | 130  | 1.6812          | 0.5687   |
+| 0.1979        | 14.0  | 140  | 1.7619          | 0.5188   |
+| 0.1694        | 15.0  | 150  | 1.6903          | 0.55     |
 
 
 ### Framework versions
 
 - Transformers 4.33.1
-- Pytorch 2.0.1+cu118
-- Datasets 2.14.5
-- Tokenizers 0.13.3
+- Pytorch 1.12.1+cu116
+- Datasets 2.4.0
+- Tokenizers 0.12.1

pytorch_model.bin

@@ -1,3 +1,3 @@
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+oid sha256:e60f4d92a21072be3aa72bee405270883b6d8f569a64c414f8b3ee9dd1504497
 size 343285425