Upload ./vision_tower-epoch-2-lr-0.0001/val_set_result.out with huggingface_hub

vision_tower-epoch-2-lr-0.0001/val_set_result.out

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+/cm/local/apps/slurm/var/spool/job24428/slurm_script: line 27: SBATCH: command not found
+/cm/local/apps/slurm/var/spool/job24428/slurm_script: line 28: SBATCH: command not found
+/home/FYP/angk0064/.conda/envs/llava-med/lib/python3.10/site-packages/transformers/utils/generic.py:441: FutureWarning: `torch.utils._pytree._register_pytree_node` is deprecated. Please use `torch.utils._pytree.register_pytree_node` instead.
+  _torch_pytree._register_pytree_node(
+/home/FYP/angk0064/.conda/envs/llava-med/lib/python3.10/site-packages/transformers/utils/generic.py:309: FutureWarning: `torch.utils._pytree._register_pytree_node` is deprecated. Please use `torch.utils._pytree.register_pytree_node` instead.
+  _torch_pytree._register_pytree_node(
+/home/FYP/angk0064/.conda/envs/llava-med/lib/python3.10/site-packages/transformers/utils/generic.py:309: FutureWarning: `torch.utils._pytree._register_pytree_node` is deprecated. Please use `torch.utils._pytree.register_pytree_node` instead.
+  _torch_pytree._register_pytree_node(
+testing out loading previously trained weights
+loading classifier
+classifier: CLIPDiseaseClassifier(
+  (mlp): Sequential(
+    (0): Linear(in_features=1024, out_features=1024, bias=True)
+    (1): ReLU()
+    (2): Dropout(p=0.5, inplace=False)
+    (3): Linear(in_features=1024, out_features=1024, bias=True)
+    (4): ReLU()
+    (5): Dropout(p=0.5, inplace=False)
+    (6): Linear(in_features=1024, out_features=56, bias=True)
+  )
+)
+vision_tower: /home/FYP/angk0064/ANGK0064/checkpoints/vision_tower-epoch-2-lr-0.0001
+self.select_feature: cls
+self.vision_tower_name: /home/FYP/angk0064/ANGK0064/checkpoints/vision_tower-epoch-2-lr-0.0001
+/home/FYP/angk0064/ANGK0064/checkpoints/vision_tower-epoch-2-lr-0.0001 is already loaded, `load_model` called again, skipping.
+vision_tower_instance: CustomCLIPVisionTower(
+  (vision_tower): CLIPVisionModel(
+    (vision_model): CLIPVisionTransformer(
+      (embeddings): CLIPVisionEmbeddings(
+        (patch_embedding): Conv2d(3, 1024, kernel_size=(14, 14), stride=(14, 14), bias=False)
+        (position_embedding): Embedding(577, 1024)
+      )
+      (pre_layrnorm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
+      (encoder): CLIPEncoder(
+        (layers): ModuleList(
+          (0-23): 24 x CLIPEncoderLayer(
+            (self_attn): CLIPAttention(
+              (k_proj): Linear(in_features=1024, out_features=1024, bias=True)
+              (v_proj): Linear(in_features=1024, out_features=1024, bias=True)
+              (q_proj): Linear(in_features=1024, out_features=1024, bias=True)
+              (out_proj): Linear(in_features=1024, out_features=1024, bias=True)
+            )
+            (layer_norm1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
+            (mlp): CLIPMLP(
+              (activation_fn): QuickGELUActivation()
+              (fc1): Linear(in_features=1024, out_features=4096, bias=True)
+              (fc2): Linear(in_features=4096, out_features=1024, bias=True)
+            )
+            (layer_norm2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
+          )
+        )
+      )
+      (post_layernorm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
+    )
+  )
+)
+vision_tower_instance: CustomCLIPVisionTower(
+  (vision_tower): CLIPVisionModel(
+    (vision_model): CLIPVisionTransformer(
+      (embeddings): CLIPVisionEmbeddings(
+        (patch_embedding): Conv2d(3, 1024, kernel_size=(14, 14), stride=(14, 14), bias=False)
+        (position_embedding): Embedding(577, 1024)
+      )
+      (pre_layrnorm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
+      (encoder): CLIPEncoder(
+        (layers): ModuleList(
+          (0-23): 24 x CLIPEncoderLayer(
+            (self_attn): CLIPAttention(
+              (k_proj): Linear(in_features=1024, out_features=1024, bias=True)
+              (v_proj): Linear(in_features=1024, out_features=1024, bias=True)
+              (q_proj): Linear(in_features=1024, out_features=1024, bias=True)
+              (out_proj): Linear(in_features=1024, out_features=1024, bias=True)
+            )
+            (layer_norm1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
+            (mlp): CLIPMLP(
+              (activation_fn): QuickGELUActivation()
+              (fc1): Linear(in_features=1024, out_features=4096, bias=True)
+              (fc2): Linear(in_features=4096, out_features=1024, bias=True)
+            )
+            (layer_norm2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
+          )
+        )
+      )
+      (post_layernorm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
+    )
+  )
+)
+len(ground_truths): 64
+ground_truths: tensor([[0., 0., 0.,  ..., 0., 0., 1.],
+        [0., 0., 0.,  ..., 0., 0., 1.],
+        [1., 0., 0.,  ..., 0., 0., 1.],
+        ...,
+        [0., 0., 0.,  ..., 0., 0., 1.],
+        [0., 0., 0.,  ..., 0., 0., 1.],
+        [0., 0., 0.,  ..., 0., 0., 1.]], device='cuda:0')
+len(ground_truths): 64
+ground_truths: tensor([[0., 0., 1.,  ..., 0., 0., 1.],
+        [0., 0., 0.,  ..., 0., 0., 1.],
+        [0., 0., 0.,  ..., 0., 1., 0.],
+        ...,
+        [1., 0., 0.,  ..., 0., 1., 0.],
+        [1., 0., 0.,  ..., 0., 0., 1.],
+        [0., 0., 0.,  ..., 0., 1., 0.]], device='cuda:0')
+len(ground_truths): 64
+ground_truths: tensor([[1., 0., 0.,  ..., 0., 0., 1.],
+        [0., 0., 1.,  ..., 0., 1., 0.],
+        [0., 0., 0.,  ..., 0., 1., 0.],
+        ...,
+        [0., 0., 0.,  ..., 0., 1., 0.],
+        [0., 0., 0.,  ..., 0., 0., 1.],
+        [0., 0., 0.,  ..., 0., 1., 0.]], device='cuda:0')
+len(ground_truths): 64
+ground_truths: tensor([[0., 0., 0.,  ..., 0., 1., 0.],
+        [0., 0., 1.,  ..., 0., 1., 0.],
+        [0., 0., 0.,  ..., 0., 0., 1.],
+        ...,
+        [0., 0., 0.,  ..., 0., 1., 0.],
+        [0., 0., 0.,  ..., 0., 1., 0.],
+        [0., 0., 0.,  ..., 0., 1., 0.]], device='cuda:0')
+len(ground_truths): 5
+ground_truths: tensor([[0., 0., 1., 0., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0.,
+         0., 1., 1., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1.,
+         0., 0., 1., 0., 0., 0., 0., 1., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0.,
+         1., 0.],
+        [0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0.,
+         0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 1., 0., 0., 0., 0., 1.,
+         0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0.,
+         0., 1.],
+        [0., 0., 0., 1., 0., 0., 1., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0.,
+         0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1.,
+         0., 0., 0., 1., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 1., 0., 0.,
+         0., 1.],
+        [0., 0., 1., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 1., 0., 0.,
+         0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1.,
+         0., 0., 1., 0., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0.,
+         0., 1.],
+        [0., 0., 1., 0., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 1.,
+         0., 0., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 1., 0., 0., 0., 0., 1.,
+         0., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 0., 0., 1., 0., 0., 0., 0.,
+         0., 1.]], device='cuda:0')
+accuracy score: 0.891351943076081
+precision score: 0.7949743003997716
+recall score: 0.7619047619047619
+f1 score: 0.7780883174958076