Reusing dataset imdb (/Users/ashvid/.cache/huggingface/datasets/imdb/plain_text/1.0.0/2fdd8b9bcadd6e7055e742a706876ba43f19faee861df134affd7a3f60fc38a1)
100%|████████████████████████████████████████████| 3/3 [00:00<00:00, 177.94it/s]
Parameter 'function'=<function tokenize_function at 0x1748fbdc0> of the transform datasets.arrow_dataset.Dataset._map_single couldn't be hashed properly, a random hash was used instead. Make sure your transforms and parameters are serializable with pickle or dill for the dataset fingerprinting and caching to work. If you reuse this transform, the caching mechanism will consider it to be different from the previous calls and recompute everything. This warning is only showed once. Subsequent hashing failures won't be showed.
100%|███████████████████████████████████████████| 25/25 [00:05<00:00,  4.96ba/s]
100%|███████████████████████████████████████████| 25/25 [00:04<00:00,  5.14ba/s]
100%|███████████████████████████████████████████| 50/50 [00:09<00:00,  5.06ba/s]
2022-07-04 12:36:03.451546: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  SSE4.2 AVX AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
Metal device set to: AMD Radeon PRO W6800

systemMemory: 64.00 GB
maxCacheSize: 14.99 GB

2022-07-04 12:36:03.452094: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:305] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support.
2022-07-04 12:36:03.452316: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:271] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: <undefined>)
Epoch 1/5
2022-07-04 12:36:12.698195: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:185] None of the MLIR Optimization Passes are enabled (registered 2)
2022-07-04 12:36:12.734888: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:112] Plugin optimizer for device_type GPU is enabled.
125/125 [==============================] - ETA: 0s - loss: 0.7356 - sparse_categorical_accuracy: 0.52402022-07-04 12:37:23.295284: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:112] Plugin optimizer for device_type GPU is enabled.
125/125 [==============================] - 103s 713ms/step - loss: 0.7356 - sparse_categorical_accuracy: 0.5240 - val_loss: 0.7057 - val_sparse_categorical_accuracy: 0.4880
Epoch 2/5
125/125 [==============================] - 87s 698ms/step - loss: 0.7090 - sparse_categorical_accuracy: 0.4980 - val_loss: 0.7165 - val_sparse_categorical_accuracy: 0.5120
Epoch 3/5
125/125 [==============================] - 87s 701ms/step - loss: 0.7047 - sparse_categorical_accuracy: 0.4880 - val_loss: 0.6948 - val_sparse_categorical_accuracy: 0.5120
Epoch 4/5
125/125 [==============================] - 118s 947ms/step - loss: 0.7072 - sparse_categorical_accuracy: 0.4950 - val_loss: 0.6932 - val_sparse_categorical_accuracy: 0.5120
Epoch 5/5
125/125 [==============================] - 111s 890ms/step - loss: 0.7005 - sparse_categorical_accuracy: 0.5060 - val_loss: 0.6944 - val_sparse_categorical_accuracy: 0.5120