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Delete vision_tower-epoch-1-lr-0.0001/val_set_result.out

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  1. vision_tower-epoch-1-lr-0.0001/val_set_result.out +0 -144
vision_tower-epoch-1-lr-0.0001/val_set_result.out DELETED
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- /cm/local/apps/slurm/var/spool/job24428/slurm_script: line 27: SBATCH: command not found
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- /cm/local/apps/slurm/var/spool/job24428/slurm_script: line 28: SBATCH: command not found
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- /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.
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- _torch_pytree._register_pytree_node(
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- /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.
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- _torch_pytree._register_pytree_node(
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- /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.
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- _torch_pytree._register_pytree_node(
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- testing out loading previously trained weights
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- loading classifier
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- classifier: CLIPDiseaseClassifier(
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- (mlp): Sequential(
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- (0): Linear(in_features=1024, out_features=1024, bias=True)
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- (1): ReLU()
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- (2): Dropout(p=0.5, inplace=False)
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- (3): Linear(in_features=1024, out_features=1024, bias=True)
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- (4): ReLU()
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- (5): Dropout(p=0.5, inplace=False)
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- (6): Linear(in_features=1024, out_features=56, bias=True)
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- )
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- )
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- vision_tower: /home/FYP/angk0064/ANGK0064/checkpoints/vision_tower-epoch-2-lr-0.0001
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- self.select_feature: cls
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- self.vision_tower_name: /home/FYP/angk0064/ANGK0064/checkpoints/vision_tower-epoch-2-lr-0.0001
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- /home/FYP/angk0064/ANGK0064/checkpoints/vision_tower-epoch-2-lr-0.0001 is already loaded, `load_model` called again, skipping.
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- vision_tower_instance: CustomCLIPVisionTower(
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- (vision_tower): CLIPVisionModel(
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- (vision_model): CLIPVisionTransformer(
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- (embeddings): CLIPVisionEmbeddings(
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- (patch_embedding): Conv2d(3, 1024, kernel_size=(14, 14), stride=(14, 14), bias=False)
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- (position_embedding): Embedding(577, 1024)
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- )
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- (pre_layrnorm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
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- (encoder): CLIPEncoder(
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- (layers): ModuleList(
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- (0-23): 24 x CLIPEncoderLayer(
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- (self_attn): CLIPAttention(
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- (k_proj): Linear(in_features=1024, out_features=1024, bias=True)
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- (v_proj): Linear(in_features=1024, out_features=1024, bias=True)
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- (q_proj): Linear(in_features=1024, out_features=1024, bias=True)
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- (out_proj): Linear(in_features=1024, out_features=1024, bias=True)
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- )
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- (layer_norm1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
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- (mlp): CLIPMLP(
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- (activation_fn): QuickGELUActivation()
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- (fc1): Linear(in_features=1024, out_features=4096, bias=True)
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- (fc2): Linear(in_features=4096, out_features=1024, bias=True)
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- )
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- (layer_norm2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
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- )
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- )
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- )
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- (post_layernorm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
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- )
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- )
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- )
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- vision_tower_instance: CustomCLIPVisionTower(
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- (vision_tower): CLIPVisionModel(
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- (vision_model): CLIPVisionTransformer(
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- (embeddings): CLIPVisionEmbeddings(
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- (patch_embedding): Conv2d(3, 1024, kernel_size=(14, 14), stride=(14, 14), bias=False)
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- (position_embedding): Embedding(577, 1024)
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- )
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- (pre_layrnorm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
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- (encoder): CLIPEncoder(
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- (layers): ModuleList(
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- (0-23): 24 x CLIPEncoderLayer(
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- (self_attn): CLIPAttention(
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- (k_proj): Linear(in_features=1024, out_features=1024, bias=True)
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- (v_proj): Linear(in_features=1024, out_features=1024, bias=True)
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- (q_proj): Linear(in_features=1024, out_features=1024, bias=True)
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- (out_proj): Linear(in_features=1024, out_features=1024, bias=True)
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- )
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- (layer_norm1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
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- (mlp): CLIPMLP(
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- (activation_fn): QuickGELUActivation()
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- (fc1): Linear(in_features=1024, out_features=4096, bias=True)
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- (fc2): Linear(in_features=4096, out_features=1024, bias=True)
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- )
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- (layer_norm2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
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- )
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- )
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- )
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- (post_layernorm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
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- )
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- )
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- )
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- len(ground_truths): 64
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- ground_truths: tensor([[0., 0., 0., ..., 0., 0., 1.],
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- [0., 0., 0., ..., 0., 0., 1.],
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- [1., 0., 0., ..., 0., 0., 1.],
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- ...,
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- [0., 0., 0., ..., 0., 0., 1.],
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- [0., 0., 0., ..., 0., 0., 1.],
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- [0., 0., 0., ..., 0., 0., 1.]], device='cuda:0')
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- len(ground_truths): 64
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- ground_truths: tensor([[0., 0., 1., ..., 0., 0., 1.],
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- [0., 0., 0., ..., 0., 0., 1.],
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- [0., 0., 0., ..., 0., 1., 0.],
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- ...,
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- [1., 0., 0., ..., 0., 1., 0.],
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- [1., 0., 0., ..., 0., 0., 1.],
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- [0., 0., 0., ..., 0., 1., 0.]], device='cuda:0')
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- len(ground_truths): 64
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- ground_truths: tensor([[1., 0., 0., ..., 0., 0., 1.],
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- [0., 0., 1., ..., 0., 1., 0.],
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- [0., 0., 0., ..., 0., 1., 0.],
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- ...,
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- [0., 0., 0., ..., 0., 1., 0.],
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- [0., 0., 0., ..., 0., 0., 1.],
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- [0., 0., 0., ..., 0., 1., 0.]], device='cuda:0')
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- len(ground_truths): 64
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- ground_truths: tensor([[0., 0., 0., ..., 0., 1., 0.],
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- [0., 0., 1., ..., 0., 1., 0.],
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- [0., 0., 0., ..., 0., 0., 1.],
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- ...,
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- [0., 0., 0., ..., 0., 1., 0.],
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- [0., 0., 0., ..., 0., 1., 0.],
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- [0., 0., 0., ..., 0., 1., 0.]], device='cuda:0')
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- len(ground_truths): 5
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- ground_truths: tensor([[0., 0., 1., 0., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0.,
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- 0., 1., 1., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1.,
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- 0., 0., 1., 0., 0., 0., 0., 1., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0.,
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- 1., 0.],
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- [0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 1., 0., 0., 0., 0., 0.,
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- 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 1., 0., 0., 0., 0., 1.,
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- 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0.,
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- 0., 1.],
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- [0., 0., 0., 1., 0., 0., 1., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0.,
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- 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1.,
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- 0., 0., 0., 1., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 1., 0., 0.,
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- 0., 1.],
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- [0., 0., 1., 0., 0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 1., 0., 0.,
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- 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1.,
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- 0., 0., 1., 0., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0.,
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- 0., 1.],
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- [0., 0., 1., 0., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 0., 1., 0., 1.,
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- 0., 0., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0., 1., 0., 0., 0., 0., 1.,
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- 0., 1., 0., 0., 0., 0., 0., 1., 0., 0., 1., 0., 0., 1., 0., 0., 0., 0.,
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- 0., 1.]], device='cuda:0')
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- accuracy score: 0.891351943076081
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- precision score: 0.7949743003997716
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- recall score: 0.7619047619047619
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- f1 score: 0.7780883174958076