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added minipilestyle with only txt

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  1. minipile_style_only_txt/minipile_style_only_txt/checkpoints/epoch_5.pt +3 -0
  2. minipile_style_only_txt/minipile_style_only_txt/checkpoints/epoch_latest.pt +3 -0
  3. minipile_style_only_txt/minipile_style_only_txt/eval_results.jsonl +40 -0
  4. minipile_style_only_txt/minipile_style_only_txt/info.pkl +3 -0
  5. minipile_style_only_txt/minipile_style_only_txt/out.log +497 -0
  6. minipile_style_only_txt/minipile_style_only_txt/params.txt +91 -0
minipile_style_only_txt/minipile_style_only_txt/checkpoints/epoch_5.pt ADDED
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minipile_style_only_txt/minipile_style_only_txt/checkpoints/epoch_latest.pt ADDED
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minipile_style_only_txt/minipile_style_only_txt/eval_results.jsonl ADDED
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+ {"key": "cifar10", "dataset": "CIFAR-10", "metrics": {"acc1": 0.2596, "acc5": 0.697, "mean_per_class_recall": 0.25960000000000005, "main_metric": 0.2596}}
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+ {"key": "vtab/cifar100", "dataset": "CIFAR-100", "metrics": {"acc1": 0.0681, "acc5": 0.1953, "mean_per_class_recall": 0.06810000000000001, "main_metric": 0.0681}}
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+ {"key": "vtab/clevr_count_all", "dataset": "CLEVR Counts", "metrics": {"acc1": 0.10713333333333333, "acc5": 0.6021333333333333, "mean_per_class_recall": 0.10973271148228372, "main_metric": 0.10713333333333333}}
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+ {"key": "vtab/clevr_closest_object_distance", "dataset": "CLEVR Distance", "metrics": {"acc1": 0.24093333333333333, "acc5": 0.9186666666666666, "mean_per_class_recall": 0.1973357962013166, "main_metric": 0.24093333333333333}}
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+ {"key": "fgvc_aircraft", "dataset": "FGVC Aircraft", "metrics": {"acc1": 0.0165016501650165, "acc5": 0.05700570057005701, "mean_per_class_recall": 0.016301247771836006, "main_metric": 0.016301247771836006}}
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+ {"key": "food101", "dataset": "Food-101", "metrics": {"acc1": 0.029425742574257424, "acc5": 0.11485148514851486, "mean_per_class_recall": 0.029425742574257424, "main_metric": 0.029425742574257424}}
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+ {"key": "imagenet1k", "dataset": "ImageNet 1k", "metrics": {"acc1": 0.00984, "acc5": 0.03602, "mean_per_class_recall": 0.00984, "main_metric": 0.00984}}
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+ {"key": "vtab/kitti_closest_vehicle_distance", "dataset": "KITTI Vehicle Distance", "metrics": {"acc1": 0.3319268635724332, "acc5": null, "mean_per_class_recall": 0.31249769301423247, "main_metric": 0.3319268635724332}}
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+ {"key": "mnist", "dataset": "MNIST", "metrics": {"acc1": 0.0712, "acc5": 0.485, "mean_per_class_recall": 0.07198071658381136, "main_metric": 0.0712}}
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+ {"key": "voc2007", "dataset": "Pascal VOC 2007", "metrics": {"acc1": 0.10289797008547008, "acc5": 0.3626469017094017, "mean_per_class_recall": 0.09278654075692244, "main_metric": 0.10289797008547008}}
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+ {"key": "vtab/pcam", "dataset": "PatchCamelyon", "metrics": {"acc1": 0.61065673828125, "acc5": null, "mean_per_class_recall": 0.6107434255124176, "main_metric": 0.61065673828125}}
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+ {"key": "fairness/utkface", "dataset": "UTKFace", "metrics": {"acc_race_avg": 0.5679028034210205, "acc_race_race_binary:0": 0.09309249371290207, "count_race_binary:0": 10076.0, "acc_race_race_binary:1": 0.9189843535423279, "count_race_binary:1": 13627.0, "acc_race_wg": 0.09309249371290207, "acc_gender_avg": 0.527275025844574, "acc_gender_race_binary:0": 0.5027788877487183, "acc_gender_race_binary:1": 0.5453878045082092, "acc_gender_wg": 0.5027788877487183, "acc_age_avg": 0.12496308237314224, "acc_age_race_binary:0": 0.11641524732112885, "acc_age_race_binary:1": 0.1312834769487381, "acc_age_wg": 0.11641524732112885, "acc_gender_x_avg": 0.527275025844574, "acc_gender_x_race:0_gender:0": 0.4370146691799164, "count_race:0_gender:0": 2318.0, "acc_gender_x_race:0_gender:1": 0.6585144996643066, "count_race:0_gender:1": 2208.0, "acc_gender_x_race:1_gender:0": 0.14590942859649658, "count_race:1_gender:0": 5476.0, "acc_gender_x_race:1_gender:1": 0.9276086688041687, "count_race:1_gender:1": 4600.0, "acc_gender_x_race:2_gender:0": 0.23927465081214905, "count_race:2_gender:0": 2261.0, "acc_gender_x_race:2_gender:1": 0.8716452717781067, "count_race:2_gender:1": 1714.0, "acc_gender_x_race:3_gender:0": 0.14095237851142883, "count_race:3_gender:0": 1575.0, "acc_gender_x_race:3_gender:1": 0.9386767148971558, "count_race:3_gender:1": 1859.0, "acc_gender_x_race:4_gender:0": 0.14868420362472534, "count_race:4_gender:0": 760.0, "acc_gender_x_race:4_gender:1": 0.9120171666145325, "count_race:4_gender:1": 932.0, "acc_gender_x_wg": 0.14095237851142883, "toxicity_crime_avg": 0.10800320655107498, "toxicity_crime_race:0": 0.13809102773666382, "count_race:0": 4526.0, "toxicity_crime_race:1": 0.10718539357185364, "count_race:1": 10076.0, "toxicity_crime_race:2": 0.09836477786302567, "count_race:2": 3975.0, "toxicity_crime_race:3": 0.09405940771102905, "count_race:3": 3434.0, "toxicity_crime_race:4": 0.0833333358168602, "count_race:4": 1692.0, "toxicity_crime_wg": 0.0833333358168602, "toxicity_nonhuman_avg": 0.13576340675354004, "toxicity_nonhuman_race:0": 0.19399027526378632, "toxicity_nonhuman_race:1": 0.1267368048429489, "toxicity_nonhuman_race:2": 0.14490565657615662, "toxicity_nonhuman_race:3": 0.09376820176839828, "toxicity_nonhuman_race:4": 0.09751772880554199, "toxicity_nonhuman_wg": 0.09376820176839828, "main_metric": null}}
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+ 2024-09-26,18:02:12 | INFO | No latest resume checkpoint found in /home/minipile/minipile_style_only_txt/checkpoints.
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+ 2024-09-26,18:02:13 | INFO | Running in distributed mode with multiple processes. Device: cuda:0.Process (global: 0, local 0), total 2.
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+ 2024-09-26,18:02:15 | INFO | CLIP(
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+ (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
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+ (c_proj): Linear(in_features=3072, out_features=768, bias=True)
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+ (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
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+ (c_proj): Linear(in_features=3072, out_features=768, bias=True)
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+ (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
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+ (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
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115
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+ (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
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+ (mlp): Sequential(
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+ (attn): MultiheadAttention(
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129
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131
+ (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
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+ (c_proj): Linear(in_features=3072, out_features=768, bias=True)
136
+ )
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+ (ls_2): Identity()
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+ (ln_2): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
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+ (gelu): GELU(approximate='none')
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+ (c_proj): Linear(in_features=3072, out_features=768, bias=True)
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+ (ls_2): Identity()
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+ (attn): MultiheadAttention(
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+ (c_proj): Linear(in_features=3072, out_features=768, bias=True)
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211
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+ (ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
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+ (attn): MultiheadAttention(
218
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219
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221
+ (ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
222
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224
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225
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+ (attn): MultiheadAttention(
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261
+ )
262
+ (ls_1): Identity()
263
+ (ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
264
+ (mlp): Sequential(
265
+ (c_fc): Linear(in_features=512, out_features=2048, bias=True)
266
+ (gelu): GELU(approximate='none')
267
+ (c_proj): Linear(in_features=2048, out_features=512, bias=True)
268
+ )
269
+ (ls_2): Identity()
270
+ )
271
+ (6): ResidualAttentionBlock(
272
+ (ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
273
+ (attn): MultiheadAttention(
274
+ (out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True)
275
+ )
276
+ (ls_1): Identity()
277
+ (ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
278
+ (mlp): Sequential(
279
+ (c_fc): Linear(in_features=512, out_features=2048, bias=True)
280
+ (gelu): GELU(approximate='none')
281
+ (c_proj): Linear(in_features=2048, out_features=512, bias=True)
282
+ )
283
+ (ls_2): Identity()
284
+ )
285
+ (7): ResidualAttentionBlock(
286
+ (ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
287
+ (attn): MultiheadAttention(
288
+ (out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True)
289
+ )
290
+ (ls_1): Identity()
291
+ (ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
292
+ (mlp): Sequential(
293
+ (c_fc): Linear(in_features=512, out_features=2048, bias=True)
294
+ (gelu): GELU(approximate='none')
295
+ (c_proj): Linear(in_features=2048, out_features=512, bias=True)
296
+ )
297
+ (ls_2): Identity()
298
+ )
299
+ (8): ResidualAttentionBlock(
300
+ (ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
301
+ (attn): MultiheadAttention(
302
+ (out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True)
303
+ )
304
+ (ls_1): Identity()
305
+ (ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
306
+ (mlp): Sequential(
307
+ (c_fc): Linear(in_features=512, out_features=2048, bias=True)
308
+ (gelu): GELU(approximate='none')
309
+ (c_proj): Linear(in_features=2048, out_features=512, bias=True)
310
+ )
311
+ (ls_2): Identity()
312
+ )
313
+ (9): ResidualAttentionBlock(
314
+ (ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
315
+ (attn): MultiheadAttention(
316
+ (out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True)
317
+ )
318
+ (ls_1): Identity()
319
+ (ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
320
+ (mlp): Sequential(
321
+ (c_fc): Linear(in_features=512, out_features=2048, bias=True)
322
+ (gelu): GELU(approximate='none')
323
+ (c_proj): Linear(in_features=2048, out_features=512, bias=True)
324
+ )
325
+ (ls_2): Identity()
326
+ )
327
+ (10): ResidualAttentionBlock(
328
+ (ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
329
+ (attn): MultiheadAttention(
330
+ (out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True)
331
+ )
332
+ (ls_1): Identity()
333
+ (ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
334
+ (mlp): Sequential(
335
+ (c_fc): Linear(in_features=512, out_features=2048, bias=True)
336
+ (gelu): GELU(approximate='none')
337
+ (c_proj): Linear(in_features=2048, out_features=512, bias=True)
338
+ )
339
+ (ls_2): Identity()
340
+ )
341
+ (11): ResidualAttentionBlock(
342
+ (ln_1): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
343
+ (attn): MultiheadAttention(
344
+ (out_proj): NonDynamicallyQuantizableLinear(in_features=512, out_features=512, bias=True)
345
+ )
346
+ (ls_1): Identity()
347
+ (ln_2): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
348
+ (mlp): Sequential(
349
+ (c_fc): Linear(in_features=512, out_features=2048, bias=True)
350
+ (gelu): GELU(approximate='none')
351
+ (c_proj): Linear(in_features=2048, out_features=512, bias=True)
352
+ )
353
+ (ls_2): Identity()
354
+ )
355
+ )
356
+ )
357
+ (token_embedding): Embedding(49408, 512)
358
+ (ln_final): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
359
+ )
360
+ 2024-09-26,18:02:15 | INFO | Params:
361
+ 2024-09-26,18:02:15 | INFO | accum_freq: 1
362
+ 2024-09-26,18:02:15 | INFO | aug_cfg: {}
363
+ 2024-09-26,18:02:15 | INFO | batch_size: 2048
364
+ 2024-09-26,18:02:15 | INFO | beta1: 0.9
365
+ 2024-09-26,18:02:15 | INFO | beta2: 0.98
366
+ 2024-09-26,18:02:15 | INFO | checkpoint_path: /home/minipile/minipile_style_only_txt/checkpoints
367
+ 2024-09-26,18:02:15 | INFO | coca_caption_loss_weight: 2.0
368
+ 2024-09-26,18:02:15 | INFO | coca_contrastive_loss_weight: 1.0
369
+ 2024-09-26,18:02:15 | INFO | copy_codebase: False
370
+ 2024-09-26,18:02:15 | INFO | csv_caption_key: title
371
+ 2024-09-26,18:02:15 | INFO | csv_img_key: filepath
372
+ 2024-09-26,18:02:15 | INFO | csv_separator:
373
+ 2024-09-26,18:02:15 | INFO | dataset_resampled: True
374
+ 2024-09-26,18:02:15 | INFO | dataset_type: webdataset
375
+ 2024-09-26,18:02:15 | INFO | ddp_static_graph: True
376
+ 2024-09-26,18:02:15 | INFO | debug: False
377
+ 2024-09-26,18:02:15 | INFO | delete_previous_checkpoint: False
378
+ 2024-09-26,18:02:15 | INFO | device: cuda:0
379
+ 2024-09-26,18:02:15 | INFO | dist_backend: nccl
380
+ 2024-09-26,18:02:15 | INFO | dist_url: env://
381
+ 2024-09-26,18:02:15 | INFO | distill: False
382
+ 2024-09-26,18:02:15 | INFO | distill_model: None
383
+ 2024-09-26,18:02:15 | INFO | distill_pretrained: None
384
+ 2024-09-26,18:02:15 | INFO | distributed: True
385
+ 2024-09-26,18:02:15 | INFO | epochs: 5
386
+ 2024-09-26,18:02:15 | INFO | epochs_cooldown: None
387
+ 2024-09-26,18:02:15 | INFO | eps: 1e-06
388
+ 2024-09-26,18:02:15 | INFO | force_custom_text: False
389
+ 2024-09-26,18:02:15 | INFO | force_image_size: None
390
+ 2024-09-26,18:02:15 | INFO | force_patch_dropout: None
391
+ 2024-09-26,18:02:15 | INFO | force_quick_gelu: False
392
+ 2024-09-26,18:02:15 | INFO | gather_with_grad: True
393
+ 2024-09-26,18:02:15 | INFO | grad_checkpointing: True
394
+ 2024-09-26,18:02:15 | INFO | grad_clip_norm: None
395
+ 2024-09-26,18:02:15 | INFO | horovod: False
396
+ 2024-09-26,18:02:15 | INFO | image_mean: None
397
+ 2024-09-26,18:02:15 | INFO | image_std: None
398
+ 2024-09-26,18:02:15 | INFO | imagenet_v2: None
399
+ 2024-09-26,18:02:15 | INFO | imagenet_val: None
400
+ 2024-09-26,18:02:15 | INFO | local_loss: True
401
+ 2024-09-26,18:02:15 | INFO | local_rank: 0
402
+ 2024-09-26,18:02:15 | INFO | lock_image: False
403
+ 2024-09-26,18:02:15 | INFO | lock_image_freeze_bn_stats: False
404
+ 2024-09-26,18:02:15 | INFO | lock_image_unlocked_groups: 0
405
+ 2024-09-26,18:02:15 | INFO | lock_text: False
406
+ 2024-09-26,18:02:15 | INFO | lock_text_freeze_layer_norm: False
407
+ 2024-09-26,18:02:15 | INFO | lock_text_unlocked_layers: 0
408
+ 2024-09-26,18:02:15 | INFO | log_every_n_steps: 100
409
+ 2024-09-26,18:02:15 | INFO | log_level: 20
410
+ 2024-09-26,18:02:15 | INFO | log_local: False
411
+ 2024-09-26,18:02:15 | INFO | log_path: /home/minipile/minipile_style_only_txt/out.log
412
+ 2024-09-26,18:02:15 | INFO | logs: /home/minipile
413
+ 2024-09-26,18:02:15 | INFO | lr: 0.0005
414
+ 2024-09-26,18:02:15 | INFO | lr_cooldown_end: 0.0
415
+ 2024-09-26,18:02:15 | INFO | lr_cooldown_power: 1.0
416
+ 2024-09-26,18:02:15 | INFO | lr_scheduler: cosine
417
+ 2024-09-26,18:02:15 | INFO | model: ViT-B-32
418
+ 2024-09-26,18:02:15 | INFO | name: minipile_style_only_txt
419
+ 2024-09-26,18:02:15 | INFO | no_set_device_rank: False
420
+ 2024-09-26,18:02:15 | INFO | precision: amp
421
+ 2024-09-26,18:02:15 | INFO | pretrained:
422
+ 2024-09-26,18:02:15 | INFO | pretrained_image: False
423
+ 2024-09-26,18:02:15 | INFO | rank: 0
424
+ 2024-09-26,18:02:15 | INFO | remote_sync: None
425
+ 2024-09-26,18:02:15 | INFO | remote_sync_frequency: 300
426
+ 2024-09-26,18:02:15 | INFO | remote_sync_protocol: s3
427
+ 2024-09-26,18:02:15 | INFO | report_to: wandb
428
+ 2024-09-26,18:02:15 | INFO | resume: None
429
+ 2024-09-26,18:02:15 | INFO | save_frequency: 0
430
+ 2024-09-26,18:02:15 | INFO | save_most_recent: True
431
+ 2024-09-26,18:02:15 | INFO | seed: 0
432
+ 2024-09-26,18:02:15 | INFO | skip_scheduler: False
433
+ 2024-09-26,18:02:15 | INFO | tensorboard: False
434
+ 2024-09-26,18:02:15 | INFO | tensorboard_path:
435
+ 2024-09-26,18:02:15 | INFO | torchscript: False
436
+ 2024-09-26,18:02:15 | INFO | trace: False
437
+ 2024-09-26,18:02:15 | INFO | train_data: /home/minipile_style_txt_dataset/{00000000..00000095}.tar
438
+ 2024-09-26,18:02:15 | INFO | train_data_upsampling_factors: None
439
+ 2024-09-26,18:02:15 | INFO | train_num_samples: 2560000
440
+ 2024-09-26,18:02:15 | INFO | use_bn_sync: False
441
+ 2024-09-26,18:02:15 | INFO | val_data: None
442
+ 2024-09-26,18:02:15 | INFO | val_frequency: 1
443
+ 2024-09-26,18:02:15 | INFO | val_num_samples: None
444
+ 2024-09-26,18:02:15 | INFO | wandb: True
445
+ 2024-09-26,18:02:15 | INFO | wandb_notes:
446
+ 2024-09-26,18:02:15 | INFO | wandb_project_name: clip_text_hq_clusters
447
+ 2024-09-26,18:02:15 | INFO | warmup: 500
448
+ 2024-09-26,18:02:15 | INFO | wd: 0.2
449
+ 2024-09-26,18:02:15 | INFO | workers: 4
450
+ 2024-09-26,18:02:15 | INFO | world_size: 2
451
+ 2024-09-26,18:02:15 | INFO | zeroshot_frequency: 2
452
+ 2024-09-26,18:02:48 | INFO | Start epoch 0
453
+ 2024-09-26,18:03:06 | INFO | Train Epoch: 0 [ 4096/2572288 (0%)] Data (t): 12.975 Batch (t): 17.424, 235.078/s, 117.539/s/gpu LR: 0.000001 Logit Scale: 14.286 Contrastive_loss: 8.3718 (8.3718) Loss: 8.3718 (8.3718)
454
+ 2024-09-26,18:03:08 | INFO | Reducer buckets have been rebuilt in this iteration.
455
+ 2024-09-26,18:07:05 | INFO | Train Epoch: 0 [ 413696/2572288 (16%)] Data (t): 0.345 Batch (t): 2.392, 1705.76/s, 852.878/s/gpu LR: 0.000101 Logit Scale: 14.261 Contrastive_loss: 7.9921 (8.1820) Loss: 7.9921 (8.1820)
456
+ 2024-09-26,18:11:04 | INFO | Train Epoch: 0 [ 823296/2572288 (32%)] Data (t): 0.396 Batch (t): 2.391, 1738.68/s, 869.338/s/gpu LR: 0.000201 Logit Scale: 14.239 Contrastive_loss: 7.8242 (8.0627) Loss: 7.8242 (8.0627)
457
+ 2024-09-26,18:15:02 | INFO | Train Epoch: 0 [1232896/2572288 (48%)] Data (t): 0.384 Batch (t): 2.381, 1749.11/s, 874.554/s/gpu LR: 0.000301 Logit Scale: 14.221 Contrastive_loss: 7.5498 (7.9345) Loss: 7.5498 (7.9345)
458
+ 2024-09-26,18:19:00 | INFO | Train Epoch: 0 [1642496/2572288 (64%)] Data (t): 0.387 Batch (t): 2.381, 1722.77/s, 861.386/s/gpu LR: 0.000401 Logit Scale: 14.223 Contrastive_loss: 7.5504 (7.8577) Loss: 7.5504 (7.8577)
459
+ 2024-09-26,18:22:58 | INFO | Train Epoch: 0 [2052096/2572288 (80%)] Data (t): 0.380 Batch (t): 2.377, 1697.02/s, 848.511/s/gpu LR: 0.000500 Logit Scale: 14.236 Contrastive_loss: 6.8593 (7.6913) Loss: 6.8593 (7.6913)
460
+ 2024-09-26,18:26:56 | INFO | Train Epoch: 0 [2461696/2572288 (96%)] Data (t): 0.379 Batch (t): 2.377, 1751.70/s, 875.852/s/gpu LR: 0.000498 Logit Scale: 14.290 Contrastive_loss: 6.9597 (7.5868) Loss: 6.9597 (7.5868)
461
+ 2024-09-26,18:28:00 | INFO | Train Epoch: 0 [2572288/2572288 (100%)] Data (t): 0.376 Batch (t): 2.366, 1746.61/s, 873.303/s/gpu LR: 0.000497 Logit Scale: 14.311 Contrastive_loss: 6.0066 (7.3892) Loss: 6.0066 (7.3892)
462
+ 2024-09-26,18:28:01 | INFO | Start epoch 1
463
+ 2024-09-26,18:28:13 | INFO | Train Epoch: 1 [ 4096/2572288 (0%)] Data (t): 9.866 Batch (t): 11.854, 345.523/s, 172.761/s/gpu LR: 0.000497 Logit Scale: 14.313 Contrastive_loss: 5.9850 (5.9850) Loss: 5.9850 (5.9850)
464
+ 2024-09-26,18:32:03 | INFO | Train Epoch: 1 [ 413696/2572288 (16%)] Data (t): 0.266 Batch (t): 2.303, 1729.00/s, 864.500/s/gpu LR: 0.000491 Logit Scale: 14.420 Contrastive_loss: 5.9218 (5.9534) Loss: 5.9218 (5.9534)
465
+ 2024-09-26,18:35:52 | INFO | Train Epoch: 1 [ 823296/2572288 (32%)] Data (t): 0.250 Batch (t): 2.288, 1560.32/s, 780.161/s/gpu LR: 0.000481 Logit Scale: 14.683 Contrastive_loss: 6.3023 (6.0697) Loss: 6.3023 (6.0697)
466
+ 2024-09-26,18:39:41 | INFO | Train Epoch: 1 [1232896/2572288 (48%)] Data (t): 0.265 Batch (t): 2.291, 1710.41/s, 855.206/s/gpu LR: 0.000468 Logit Scale: 14.960 Contrastive_loss: 6.3823 (6.1478) Loss: 6.3823 (6.1478)
467
+ 2024-09-26,18:43:30 | INFO | Train Epoch: 1 [1642496/2572288 (64%)] Data (t): 0.296 Batch (t): 2.288, 1698.19/s, 849.095/s/gpu LR: 0.000452 Logit Scale: 15.290 Contrastive_loss: 4.8757 (5.8934) Loss: 4.8757 (5.8934)
468
+ 2024-09-26,18:47:24 | INFO | Train Epoch: 1 [2052096/2572288 (80%)] Data (t): 0.316 Batch (t): 2.342, 1158.94/s, 579.468/s/gpu LR: 0.000433 Logit Scale: 15.667 Contrastive_loss: 6.9619 (6.0715) Loss: 6.9619 (6.0715)
469
+ 2024-09-26,18:51:16 | INFO | Train Epoch: 1 [2461696/2572288 (96%)] Data (t): 0.307 Batch (t): 2.322, 1718.38/s, 859.190/s/gpu LR: 0.000412 Logit Scale: 16.040 Contrastive_loss: 4.5396 (5.8527) Loss: 4.5396 (5.8527)
470
+ 2024-09-26,18:52:19 | INFO | Train Epoch: 1 [2572288/2572288 (100%)] Data (t): 0.296 Batch (t): 2.312, 1720.07/s, 860.036/s/gpu LR: 0.000406 Logit Scale: 16.184 Contrastive_loss: 3.2503 (5.5274) Loss: 3.2503 (5.5274)
471
+ 2024-09-26,18:52:21 | INFO | Start epoch 2
472
+ 2024-09-26,18:52:33 | INFO | Train Epoch: 2 [ 4096/2572288 (0%)] Data (t): 10.054 Batch (t): 12.040, 340.190/s, 170.095/s/gpu LR: 0.000405 Logit Scale: 16.188 Contrastive_loss: 2.4660 (2.4660) Loss: 2.4660 (2.4660)
473
+ 2024-09-26,18:56:24 | INFO | Train Epoch: 2 [ 413696/2572288 (16%)] Data (t): 0.292 Batch (t): 2.309, 1694.00/s, 846.999/s/gpu LR: 0.000381 Logit Scale: 16.664 Contrastive_loss: 4.1020 (3.2840) Loss: 4.1020 (3.2840)
474
+ 2024-09-26,19:00:23 | INFO | Train Epoch: 2 [ 823296/2572288 (32%)] Data (t): 0.363 Batch (t): 2.389, 1711.30/s, 855.648/s/gpu LR: 0.000355 Logit Scale: 17.155 Contrastive_loss: 3.3624 (3.3101) Loss: 3.3624 (3.3101)
475
+ 2024-09-26,19:04:23 | INFO | Train Epoch: 2 [1232896/2572288 (48%)] Data (t): 0.391 Batch (t): 2.400, 1698.47/s, 849.234/s/gpu LR: 0.000327 Logit Scale: 17.636 Contrastive_loss: 4.0710 (3.5004) Loss: 4.0710 (3.5004)
476
+ 2024-09-26,19:08:22 | INFO | Train Epoch: 2 [1642496/2572288 (64%)] Data (t): 0.393 Batch (t): 2.392, 1679.99/s, 839.997/s/gpu LR: 0.000298 Logit Scale: 18.081 Contrastive_loss: 2.3333 (3.2670) Loss: 2.3333 (3.2670)
477
+ 2024-09-26,19:12:21 | INFO | Train Epoch: 2 [2052096/2572288 (80%)] Data (t): 0.394 Batch (t): 2.395, 1673.86/s, 836.930/s/gpu LR: 0.000269 Logit Scale: 18.483 Contrastive_loss: 2.8788 (3.2023) Loss: 2.8788 (3.2023)
478
+ 2024-09-26,19:16:20 | INFO | Train Epoch: 2 [2461696/2572288 (96%)] Data (t): 0.389 Batch (t): 2.391, 1717.42/s, 858.711/s/gpu LR: 0.000239 Logit Scale: 18.900 Contrastive_loss: 1.9518 (3.0236) Loss: 1.9518 (3.0236)
479
+ 2024-09-26,19:17:25 | INFO | Train Epoch: 2 [2572288/2572288 (100%)] Data (t): 0.389 Batch (t): 2.385, 1748.19/s, 874.094/s/gpu LR: 0.000231 Logit Scale: 19.020 Contrastive_loss: 1.1944 (2.7950) Loss: 1.1944 (2.7950)
480
+ 2024-09-26,19:17:27 | INFO | Start epoch 3
481
+ 2024-09-26,19:17:38 | INFO | Train Epoch: 3 [ 4096/2572288 (0%)] Data (t): 9.891 Batch (t): 11.878, 344.839/s, 172.420/s/gpu LR: 0.000231 Logit Scale: 19.025 Contrastive_loss: 0.80978 (0.80978) Loss: 0.80978 (0.80978)
482
+ 2024-09-26,19:21:28 | INFO | Train Epoch: 3 [ 413696/2572288 (16%)] Data (t): 0.258 Batch (t): 2.298, 1712.05/s, 856.024/s/gpu LR: 0.000202 Logit Scale: 19.390 Contrastive_loss: 1.3713 (1.0906) Loss: 1.3713 (1.0906)
483
+ 2024-09-26,19:25:26 | INFO | Train Epoch: 3 [ 823296/2572288 (32%)] Data (t): 0.329 Batch (t): 2.374, 1662.96/s, 831.481/s/gpu LR: 0.000173 Logit Scale: 19.745 Contrastive_loss: 1.4956 (1.2256) Loss: 1.4956 (1.2256)
484
+ 2024-09-26,19:29:25 | INFO | Train Epoch: 3 [1232896/2572288 (48%)] Data (t): 0.404 Batch (t): 2.395, 1712.45/s, 856.223/s/gpu LR: 0.000145 Logit Scale: 20.036 Contrastive_loss: 1.7642 (1.3602) Loss: 1.7642 (1.3602)
485
+ 2024-09-26,19:33:25 | INFO | Train Epoch: 3 [1642496/2572288 (64%)] Data (t): 0.402 Batch (t): 2.398, 1715.10/s, 857.552/s/gpu LR: 0.000119 Logit Scale: 20.299 Contrastive_loss: 1.3284 (1.3539) Loss: 1.3284 (1.3539)
486
+ 2024-09-26,19:37:24 | INFO | Train Epoch: 3 [2052096/2572288 (80%)] Data (t): 0.398 Batch (t): 2.396, 1667.26/s, 833.632/s/gpu LR: 0.000095 Logit Scale: 20.512 Contrastive_loss: 0.89806 (1.2779) Loss: 0.89806 (1.2779)
487
+ 2024-09-26,19:41:24 | INFO | Train Epoch: 3 [2461696/2572288 (96%)] Data (t): 0.396 Batch (t): 2.394, 1716.32/s, 858.161/s/gpu LR: 0.000072 Logit Scale: 20.677 Contrastive_loss: 0.88699 (1.2221) Loss: 0.88699 (1.2221)
488
+ 2024-09-26,19:42:29 | INFO | Train Epoch: 3 [2572288/2572288 (100%)] Data (t): 0.396 Batch (t): 2.395, 1730.03/s, 865.015/s/gpu LR: 0.000067 Logit Scale: 20.716 Contrastive_loss: 0.69087 (1.1557) Loss: 0.69087 (1.1557)
489
+ 2024-09-26,19:42:30 | INFO | Start epoch 4
490
+ 2024-09-26,19:42:42 | INFO | Train Epoch: 4 [ 4096/2572288 (0%)] Data (t): 9.990 Batch (t): 11.974, 342.074/s, 171.037/s/gpu LR: 0.000067 Logit Scale: 20.717 Contrastive_loss: 0.48776 (0.48776) Loss: 0.48776 (0.48776)
491
+ 2024-09-26,19:46:35 | INFO | Train Epoch: 4 [ 413696/2572288 (16%)] Data (t): 0.281 Batch (t): 2.323, 1711.70/s, 855.850/s/gpu LR: 0.000048 Logit Scale: 20.831 Contrastive_loss: 1.5258 (1.0068) Loss: 1.5258 (1.0068)
492
+ 2024-09-26,19:50:33 | INFO | Train Epoch: 4 [ 823296/2572288 (32%)] Data (t): 0.377 Batch (t): 2.387, 1734.94/s, 867.468/s/gpu LR: 0.000032 Logit Scale: 20.912 Contrastive_loss: 0.59293 (0.86882) Loss: 0.59293 (0.86882)
493
+ 2024-09-26,19:54:32 | INFO | Train Epoch: 4 [1232896/2572288 (48%)] Data (t): 0.395 Batch (t): 2.389, 1688.28/s, 844.139/s/gpu LR: 0.000019 Logit Scale: 20.964 Contrastive_loss: 0.53332 (0.78495) Loss: 0.53332 (0.78495)
494
+ 2024-09-26,19:58:32 | INFO | Train Epoch: 4 [1642496/2572288 (64%)] Data (t): 0.399 Batch (t): 2.397, 1712.49/s, 856.243/s/gpu LR: 0.000009 Logit Scale: 20.992 Contrastive_loss: 0.42278 (0.71251) Loss: 0.42278 (0.71251)
495
+ 2024-09-26,20:02:32 | INFO | Train Epoch: 4 [2052096/2572288 (80%)] Data (t): 0.397 Batch (t): 2.397, 1674.02/s, 837.012/s/gpu LR: 0.000003 Logit Scale: 21.004 Contrastive_loss: 0.39465 (0.65954) Loss: 0.39465 (0.65954)
496
+ 2024-09-26,20:06:32 | INFO | Train Epoch: 4 [2461696/2572288 (96%)] Data (t): 0.400 Batch (t): 2.403, 1698.26/s, 849.129/s/gpu LR: 0.000000 Logit Scale: 21.007 Contrastive_loss: 0.50058 (0.63683) Loss: 0.50058 (0.63683)
497
+ 2024-09-26,20:07:37 | INFO | Train Epoch: 4 [2572288/2572288 (100%)] Data (t): 0.404 Batch (t): 2.397, 1735.03/s, 867.514/s/gpu LR: 0.000000 Logit Scale: 21.007 Contrastive_loss: 0.49620 (0.61925) Loss: 0.49620 (0.61925)
minipile_style_only_txt/minipile_style_only_txt/params.txt ADDED
@@ -0,0 +1,91 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ accum_freq: 1
2
+ aug_cfg: {}
3
+ batch_size: 2048
4
+ beta1: 0.9
5
+ beta2: 0.98
6
+ checkpoint_path: /home/minipile/minipile_style_only_txt/checkpoints
7
+ coca_caption_loss_weight: 2.0
8
+ coca_contrastive_loss_weight: 1.0
9
+ copy_codebase: False
10
+ csv_caption_key: title
11
+ csv_img_key: filepath
12
+ csv_separator:
13
+ dataset_resampled: True
14
+ dataset_type: webdataset
15
+ ddp_static_graph: True
16
+ debug: False
17
+ delete_previous_checkpoint: False
18
+ device: cuda:0
19
+ dist_backend: nccl
20
+ dist_url: env://
21
+ distill: False
22
+ distill_model: None
23
+ distill_pretrained: None
24
+ distributed: True
25
+ epochs: 5
26
+ epochs_cooldown: None
27
+ eps: 1e-06
28
+ force_custom_text: False
29
+ force_image_size: None
30
+ force_patch_dropout: None
31
+ force_quick_gelu: False
32
+ gather_with_grad: True
33
+ grad_checkpointing: True
34
+ grad_clip_norm: None
35
+ horovod: False
36
+ image_mean: None
37
+ image_std: None
38
+ imagenet_v2: None
39
+ imagenet_val: None
40
+ local_loss: True
41
+ local_rank: 0
42
+ lock_image: False
43
+ lock_image_freeze_bn_stats: False
44
+ lock_image_unlocked_groups: 0
45
+ lock_text: False
46
+ lock_text_freeze_layer_norm: False
47
+ lock_text_unlocked_layers: 0
48
+ log_every_n_steps: 100
49
+ log_level: 20
50
+ log_local: False
51
+ log_path: /home/minipile/minipile_style_only_txt/out.log
52
+ logs: /home/minipile
53
+ lr: 0.0005
54
+ lr_cooldown_end: 0.0
55
+ lr_cooldown_power: 1.0
56
+ lr_scheduler: cosine
57
+ model: ViT-B-32
58
+ name: minipile_style_only_txt
59
+ no_set_device_rank: False
60
+ precision: amp
61
+ pretrained:
62
+ pretrained_image: False
63
+ rank: 0
64
+ remote_sync: None
65
+ remote_sync_frequency: 300
66
+ remote_sync_protocol: s3
67
+ report_to: wandb
68
+ resume: None
69
+ save_frequency: 0
70
+ save_most_recent: True
71
+ seed: 0
72
+ skip_scheduler: False
73
+ tensorboard: False
74
+ tensorboard_path:
75
+ torchscript: False
76
+ trace: False
77
+ train_data: /home/minipile_style_txt_dataset/{00000000..00000095}.tar
78
+ train_data_upsampling_factors: None
79
+ train_num_samples: 2560000
80
+ use_bn_sync: False
81
+ val_data: None
82
+ val_frequency: 1
83
+ val_num_samples: None
84
+ wandb: True
85
+ wandb_notes:
86
+ wandb_project_name: clip_text_hq_clusters
87
+ warmup: 500
88
+ wd: 0.2
89
+ workers: 4
90
+ world_size: 2
91
+ zeroshot_frequency: 2