insert_at_4_nonfrozen_50rn_8heads_k=128.ckpt

  • Final validation scores: acc@1=0.758 acc@5=0.92
  • Trained for 4 epochs
# lightning.pytorch==2.0.0
seed_everything: true
trainer:
  callbacks:
    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
      init_args:
        save_last: true
        save_top_k: 1
        monitor: v_c_loss
    - class_path: lightning.pytorch.callbacks.LearningRateMonitor
  accelerator: auto
  strategy: auto
  devices: auto
  num_nodes: 1
  precision: 16-mixed
  logger: null
  fast_dev_run: false
  max_epochs: 8
  min_epochs: null
  max_steps: -1
  min_steps: null
  max_time: null
  limit_train_batches: null
  limit_val_batches: null
  limit_test_batches: null
  limit_predict_batches: null
  overfit_batches: 0.0
  val_check_interval: 0.1
  check_val_every_n_epoch: 1
  num_sanity_val_steps: null
  log_every_n_steps: 15
  enable_checkpointing: true
  enable_progress_bar: null
  enable_model_summary: null
  accumulate_grad_batches: 1
  gradient_clip_val: 1.0
  gradient_clip_algorithm: null
  deterministic: null
  benchmark: null
  inference_mode: true
  use_distributed_sampler: true
  profiler: null
  detect_anomaly: false
  barebones: false
  plugins: null
  sync_batchnorm: false
  reload_dataloaders_every_n_epochs: 0
  default_root_dir: ckpt/insert_at_4_nonfrozen_50rn_4heads_k=128
model:
  resnet_type: 50
  is_rq: false
  quantizer_args:
    heads: 8
    use_cosine_sim: false
    accept_image_fmap: true
    codebook_dim: 256
    codebook_size: 128
    decay: 0.95
    eps: 1.0e-05
    commitment_weight: 0.0
    threshold_ema_dead_code: 2
  resnet_insertion_index: 4
  unfreeze_resnet_block_indeces: [3]
  unfreeze_fc: true
  lr: 0.00010
data:
  data_dir: "/home/figes/Downloads/ILSVRC2012_CLS-LOC/"
  image_size: 224
  num_workers: 6
  batch_size: 512
  shuffle: true
  pin_memory: true
  drop_last: false

epoch0-insert-at-4-frozen-deep-norq.ckpt

  • trained to vall acc@5 0.887 acc@1 .6697
  • big codebook size (256)
  • 8 heads
# lightning.pytorch==2.0.0
# bigger depth
seed_everything: true
trainer:
  callbacks:
    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
      init_args:
        save_last: true
        save_top_k: 1
        monitor: v_c_loss
  accelerator: auto
  strategy: auto
  devices: auto
  num_nodes: 1
  precision: 16-mixed
  logger: null
  callbacks: null
  fast_dev_run: false
  max_epochs: 5
  min_epochs: null
  max_steps: -1
  min_steps: null
  max_time: null
  limit_train_batches: null
  limit_val_batches: null
  limit_test_batches: null
  limit_predict_batches: null
  overfit_batches: 0.0
  val_check_interval: 0.1
  check_val_every_n_epoch: 1
  num_sanity_val_steps: null
  log_every_n_steps: 15
  enable_checkpointing: true
  enable_progress_bar: null
  enable_model_summary: null
  accumulate_grad_batches: 1
  gradient_clip_val: 1.0
  gradient_clip_algorithm: null
  deterministic: null
  benchmark: null
  inference_mode: true
  use_distributed_sampler: true
  profiler: null
  detect_anomaly: false
  barebones: false
  plugins: null
  sync_batchnorm: false
  reload_dataloaders_every_n_epochs: 0
  default_root_dir: ckpt/insert_at_4_frozen_deep
model:
  resnet_type: 34
  is_rq: false
  quantizer_args:
    heads: 8
    use_cosine_sim: false
    accept_image_fmap: true
    codebook_dim: 128
    codebook_size: 256
    decay: 0.85
    eps: 1.0e-05
    commitment_weight: 5.0
    threshold_ema_dead_code: 1
  resnet_insertion_index: 4
  unfreeze_resnet_block_indeces: []
  unfreeze_fc: false
  lr: 0.0002
data:
  data_dir: "/home/figes/Downloads/ILSVRC2012_CLS-LOC/"
  image_size: 224
  num_workers: 6
  batch_size: 512
  shuffle: true
  pin_memory: true
  drop_last: false

insert_at_4_nonfrozen_deep_epoch=3-step=7759.ckpt

  • small codebook size (64)
  • trained to v acc@5 .8645 acc@1 0.6554
# lightning.pytorch==2.0.0
# bigger depth
seed_everything: true
trainer:
  callbacks:
    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
      init_args:
        save_last: true
        save_top_k: 1
        monitor: v_c_loss
  accelerator: auto
  strategy: auto
  devices: auto
  num_nodes: 1
  precision: 16-mixed
  logger: null
  callbacks: null
  fast_dev_run: false
  max_epochs: 5
  min_epochs: null
  max_steps: -1
  min_steps: null
  max_time: null
  limit_train_batches: null
  limit_val_batches: null
  limit_test_batches: null
  limit_predict_batches: null
  overfit_batches: 0.0
  val_check_interval: 0.1
  check_val_every_n_epoch: 1
  num_sanity_val_steps: null
  log_every_n_steps: 15
  enable_checkpointing: true
  enable_progress_bar: null
  enable_model_summary: null
  accumulate_grad_batches: 1
  gradient_clip_val: 1.0
  gradient_clip_algorithm: null
  deterministic: null
  benchmark: null
  inference_mode: true
  use_distributed_sampler: true
  profiler: null
  detect_anomaly: false
  barebones: false
  plugins: null
  sync_batchnorm: false
  reload_dataloaders_every_n_epochs: 0
  default_root_dir: ckpt/insert_at_4_nonfrozen_deep
model:
  resnet_type: 34
  is_rq: false
  quantizer_args:
    heads: 8
    use_cosine_sim: false
    accept_image_fmap: true
    codebook_dim: 128
    codebook_size: 64
    decay: 0.85
    eps: 1.0e-05
    commitment_weight: 0.5
    threshold_ema_dead_code: 1
    sample_codebook_temp: 0.1
  resnet_insertion_index: 4
  unfreeze_resnet_block_indeces:
    - 2
    - 3
  unfreeze_fc: true
  lr: 0.0001
data:
  data_dir: "/home/figes/Downloads/ILSVRC2012_CLS-LOC/"
  image_size: 224
  num_workers: 6
  batch_size: 512
  shuffle: true
  pin_memory: true
  drop_last: false

epoch=1-step=4503.ckpt

  • inserted at 3, all resnet weights frozen
  • ~.62 val acc
# lightning.pytorch==2.0.0
seed_everything: true
trainer:
  callbacks:
    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
      init_args:
        save_last: true
        save_top_k: 1
        monitor: v_c_loss
  accelerator: auto
  strategy: auto
  devices: auto
  num_nodes: 1
  precision: 16-mixed
  logger: null
  callbacks: null
  fast_dev_run: false
  max_epochs: 10
  min_epochs: null
  max_steps: -1
  min_steps: null
  max_time: null
  limit_train_batches: null
  limit_val_batches: null
  limit_test_batches: null
  limit_predict_batches: null
  overfit_batches: 0.0
  val_check_interval: 0.1
  check_val_every_n_epoch: 1
  num_sanity_val_steps: null
  log_every_n_steps: 5
  enable_checkpointing: true
  enable_progress_bar: null
  enable_model_summary: null
  accumulate_grad_batches: 1
  gradient_clip_val: 0.5
  gradient_clip_algorithm: null
  deterministic: null
  benchmark: null
  inference_mode: true
  use_distributed_sampler: true
  profiler: null
  detect_anomaly: false
  barebones: false
  plugins: null
  sync_batchnorm: false
  reload_dataloaders_every_n_epochs: 0
  default_root_dir: ckpt/test_insert_at_3_frozen
model:
  resnet_type: 34
  is_rq: true
  quantizer_args:
    num_quantizers: 4
    shared_codebook: false
    quantize_dropout: true
    accept_image_fmap: true
    codebook_dim: 128
    codebook_size: 512
    decay: 0.85
    eps: 1.0e-05
    commitment_weight: 25.0
    threshold_ema_dead_code: 2
    sample_codebook_temp: 0.05
    quantize_dropout_cutoff_index: 1
    quantize_dropout_multiple_of: 1
  resnet_insertion_index: 3
  lr: 0.0002
data:
  data_dir: "/home/figes/Downloads/ILSVRC2012_CLS-LOC/"
  image_size: 224
  num_workers: 8
  batch_size: 512
  shuffle: true
  pin_memory: true
  drop_last: false

epoch2-val-63.ckpt

  • final val acc .63
  • trained for 2 epochs
  • More compressed embedding space, with more dropout
  • git commit dc54a9bdbfcfbc83c736ac5c06ab09c5acf2d5e8
# lightning.pytorch==2.0.0
seed_everything: true
trainer:
  callbacks:
    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
      init_args:
        save_last: true
        save_top_k: 1
        monitor: v_c_loss
  accelerator: auto
  strategy: auto
  devices: auto
  num_nodes: 1
  precision: 16-mixed
  logger: null
  callbacks: null
  fast_dev_run: false
  max_epochs: 10
  min_epochs: null
  max_steps: -1
  min_steps: null
  max_time: null
  limit_train_batches: null
  limit_val_batches: null
  limit_test_batches: null
  limit_predict_batches: null
  overfit_batches: 0.0
  val_check_interval: 0.1
  check_val_every_n_epoch: 1
  num_sanity_val_steps: null
  log_every_n_steps: 5
  enable_checkpointing: true
  enable_progress_bar: null
  enable_model_summary: null
  accumulate_grad_batches: 1
  gradient_clip_val: 0.5
  gradient_clip_algorithm: null
  deterministic: null
  benchmark: null
  inference_mode: true
  use_distributed_sampler: true
  profiler: null
  detect_anomaly: false
  barebones: false
  plugins: null
  sync_batchnorm: false
  reload_dataloaders_every_n_epochs: 0
  default_root_dir: ckpt/insert_at_4
model:
  resnet_type: 34
  is_rq: true
  quantizer_args:
    num_quantizers: 8
    shared_codebook: true
    quantize_dropout: false
    accept_image_fmap: true
    codebook_dim: 128
    codebook_size: 64
    decay: 0.8
    eps: 1.0e-05
    commitment_weight: 5.0
    threshold_ema_dead_code: 1
    sample_codebook_temp: 0.1
  resnet_insertion_index: 4
  unfreeze_resnet_block_indeces:
    - 3
  unfreeze_fc: true
  lr: 0.0002
data:
  data_dir: "/home/figes/Downloads/ILSVRC2012_CLS-LOC/"
  image_size: 224
  num_workers: 6
  batch_size: 512
  shuffle: true
  pin_memory: true
  drop_last: false

epoch=5-step=14765.ckpt

  • trained for 5 1/2 epochs on imagenet, on top of resnet 34
  • final validation accuracy: .66
  • final training accuracy: 0.64
  • git hash: c4852331f9a40393b8ffd8b7b9a689d1ff6e1021
  • config:
# lightning.pytorch==2.0.0
seed_everything: true
trainer:
  callbacks:
    - class_path: lightning.pytorch.callbacks.ModelCheckpoint
      init_args:
        save_last: true
        save_top_k: 1
        monitor: v_c_loss
  accelerator: auto
  strategy: auto
  devices: auto
  num_nodes: 1
  precision: 16-mixed
  logger: null
  callbacks: null
  fast_dev_run: false
  max_epochs: 10
  min_epochs: null
  max_steps: -1
  min_steps: null
  max_time: null
  limit_train_batches: null
  limit_val_batches: null
  limit_test_batches: null
  limit_predict_batches: null
  overfit_batches: 0.0
  val_check_interval: 0.1
  check_val_every_n_epoch: 1
  num_sanity_val_steps: null
  log_every_n_steps: 5
  enable_checkpointing: true
  enable_progress_bar: null
  enable_model_summary: null
  accumulate_grad_batches: 1
  gradient_clip_val: 0.5
  gradient_clip_algorithm: null
  deterministic: null
  benchmark: null
  inference_mode: true
  use_distributed_sampler: true
  profiler: null
  detect_anomaly: false
  barebones: false
  plugins: null
  sync_batchnorm: false
  reload_dataloaders_every_n_epochs: 0
  default_root_dir: ckpt/test_insert_at_4
model:
  resnet_type: 34
  is_rq: true
  quantizer_args:
    num_quantizers: 4
    shared_codebook: true
    quantize_dropout: false
    accept_image_fmap: true
    codebook_dim: 128
    codebook_size: 256
    decay: 0.8
    eps: 1.0e-05
    commitment_weight: 5.0
    threshold_ema_dead_code: 1
    sample_codebook_temp: 0.0
  resnet_insertion_index: 4
  unfreeze_resnet_block_indeces:
    - 3
  unfreeze_fc: true
  lr: 0.0002
data:
  data_dir: "/home/figes/Downloads/ILSVRC2012_CLS-LOC/"
  image_size: 224
  num_workers: 8
  batch_size: 512
  shuffle: true
  pin_memory: true
  drop_last: false
Downloads last month

-

Downloads are not tracked for this model. How to track
Inference Providers NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API: The model has no library tag.