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Training in progress, step 125

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  1. benchmarks.shelve.dat +0 -0
  2. logs/harness_benchmarks=tinyBenchmarks, learning_rate=0.0001, lr_scheduler_kwargs=__power___0.7___lr_end___2e-05_, lr_scheduler_type=polynomial, per_device_train_batch_size=8, warmup_ratio=0.1/events.out.tfevents.1727036925.1c1a426a2fee +3 -0
  3. logs/harness_benchmarks=tinyBenchmarks, learning_rate=0.0001, lr_scheduler_kwargs=__power___0.7___lr_end___2e-05_, lr_scheduler_type=polynomial, per_device_train_batch_size=8/events.out.tfevents.1727036012.1c1a426a2fee +3 -0
  4. logs/harness_benchmarks=tinyBenchmarks, learning_rate=0.0001, lr_scheduler_kwargs=__power___0.7___lr_end___2e-05_, lr_scheduler_type=polynomial, per_device_train_batch_size=8/events.out.tfevents.1727036850.1c1a426a2fee +3 -0
  5. logs/harness_benchmarks=tinyBenchmarks, learning_rate=0.0001, lr_scheduler_kwargs=__power___0.7___lr_end___2e-05_, lr_scheduler_type=polynomial, per_device_train_batch_size=8/events.out.tfevents.1727060443.1c1a426a2fee +3 -0
  6. model.safetensors +1 -1
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