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20220713-h14m38s16_example_conll2003

Token Classification
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distilbert
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  1. README.md +59 -0
  2. runs.json +196 -0
  3. tensorboard/1657723101.607428/events.out.tfevents.1657723101.ip-10-0-202-165.ec2.internal.1.1 +3 -0
  4. tensorboard/1657723101.608861/events.out.tfevents.1657723101.ip-10-0-202-165.ec2.internal.1.2 +3 -0
  5. tensorboard/events.out.tfevents.1657723101.ip-10-0-202-165.ec2.internal.1.0 +3 -0
README.md ADDED
@@ -0,0 +1,59 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ pipeline_tag: token-classification
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+ datasets:
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+ - conll2003
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ tags:
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+ - distilbert
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+ ---
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+
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+ **task**: `token-classification`
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+ **Backend:** `sagemaker-training`
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+ **Backend args:** `{'instance_type': 'ml.g4dn.2xlarge', 'supported_instructions': None}`
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+ **Number of evaluation samples:** `All dataset`
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+
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+ Fixed parameters:
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+ * **model_name_or_path**: `elastic/distilbert-base-uncased-finetuned-conll03-english`
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+ * **dataset**:
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+ * **path**: `conll2003`
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+ * **eval_split**: `validation`
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+ * **data_keys**: `{'primary': 'tokens'}`
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+ * **ref_keys**: `['ner_tags']`
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+ * **calibration_split**: `train`
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+ * **quantization_approach**: `static`
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+ * **operators_to_quantize**: `['Add', 'MatMul']`
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+ * **per_channel**: `False`
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+ * **calibration**:
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+ * **method**: `minmax`
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+ * **num_calibration_samples**: `100`
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+ * **framework**: `onnxruntime`
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+ * **framework_args**:
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+ * **opset**: `11`
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+ * **optimization_level**: `1`
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+ * **aware_training**: `False`
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+
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+ Benchmarked parameters:
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+ * **node_exclusion**: `[]`, `['layernorm', 'gelu', 'residual', 'gather', 'softmax']`
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+
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+ # Evaluation
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+ ## Non-time metrics
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+ | node_exclusion | | precision (original) | precision (optimized) | | recall (original) | recall (optimized) | | f1 (original) | f1 (optimized) | | accuracy (original) | accuracy (optimized) |
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+ | :------------------------------------------------------: | :-: | :------------------: | :-------------------: | :-: | :---------------: | :----------------: | :-: | :-----------: | :------------: | :-: | :-----------------: | :------------------: |
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+ | `['layernorm', 'gelu', 'residual', 'gather', 'softmax']` | \| | 0.936 | 0.904 | \| | 0.944 | 0.921 | \| | 0.940 | 0.912 | \| | 0.988 | 0.984 |
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+ | `[]` | \| | 0.936 | 0.065 | \| | 0.944 | 0.243 | \| | 0.940 | 0.103 | \| | 0.988 | 0.357 |
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+
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+ ## Time metrics
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+ Time benchmarks were run for 15 seconds per config.
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+
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+
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+ Below, time metrics for batch size = 4, input length = 64.
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+
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+ | node_exclusion | | latency_mean (original, ms) | latency_mean (optimized, ms) | | throughput (original, /s) | throughput (optimized, /s) |
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+ | :------------------------------------------------------: | :-: | :-------------------------: | :--------------------------: | :-: | :-----------------------: | :------------------------: |
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+ | `['layernorm', 'gelu', 'residual', 'gather', 'softmax']` | \| | 114.51 | 53.59 | \| | 8.73 | 18.67 |
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+ | `[]` | \| | 90.67 | 59.55 | \| | 11.07 | 16.87 |
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+
runs.json ADDED
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+ [
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+ {
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+ "model_name_or_path": "elastic/distilbert-base-uncased-finetuned-conll03-english",
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+ "task": "token-classification",
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+ "task_args": null,
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+ "dataset": {
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+ "path": "conll2003",
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+ "eval_split": "validation",
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+ "data_keys": {
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+ "primary": "tokens",
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+ "secondary": null
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+ },
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+ "ref_keys": [
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+ "ner_tags"
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+ ],
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+ "name": null,
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+ "calibration_split": "train"
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+ },
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+ "quantization_approach": "static",
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+ "operators_to_quantize": [
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+ "Add",
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+ "MatMul"
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+ ],
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+ "node_exclusion": [
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+ "layernorm",
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+ "gelu",
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+ "residual",
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+ "gather",
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+ "softmax"
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+ ],
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+ "aware_training": false,
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+ "per_channel": false,
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+ "calibration": {
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+ "method": "minmax",
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+ "num_calibration_samples": 100,
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+ "calibration_histogram_percentile": null,
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+ "calibration_moving_average": null,
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+ "calibration_moving_average_constant": null
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+ },
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+ "framework": "onnxruntime",
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+ "framework_args": {
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+ "opset": 11,
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+ "optimization_level": 1
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+ },
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+ "hardware": "Architecture: x86_64\nCPU op-mode(s): 32-bit, 64-bit\nByte Order: Little Endian\nAddress sizes: 46 bits physical, 48 bits virtual\nCPU(s): 8\nOn-line CPU(s) list: 0-7\nThread(s) per core: 2\nCore(s) per socket: 4\nSocket(s): 1\nNUMA node(s): 1\nVendor ID: GenuineIntel\nCPU family: 6\nModel: 85\nModel name: Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz\nStepping: 7\nCPU MHz: 3099.511\nBogoMIPS: 4999.99\nHypervisor vendor: KVM\nVirtualization type: full\nL1d cache: 128 KiB\nL1i cache: 128 KiB\nL2 cache: 4 MiB\nL3 cache: 35.8 MiB\nNUMA node0 CPU(s): 0-7\nVulnerability Itlb multihit: KVM: Vulnerable\nVulnerability L1tf: Mitigation; PTE Inversion\nVulnerability Mds: Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown\nVulnerability Meltdown: Mitigation; PTI\nVulnerability Spec store bypass: Vulnerable\nVulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2: Mitigation; Retpolines, STIBP disabled, RSB filling\nVulnerability Srbds: Not affected\nVulnerability Tsx async abort: Not affected\nFlags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single pti fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves ida arat pku ospke avx512_vnni\n",
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+ "versions": {
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+ "transformers": "4.20.1",
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+ "optimum": "1.2.3.dev0",
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+ "optimum_hash": "6911cc6576c9fd373dfdba597e7a6b3ec37c2063"
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+ {
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+ "batch_size": 4,
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+ "input_length": 64,
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+ "baseline": {
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+ "nb_forwards": 131,
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+ "throughput": 8.73,
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+ "latency_mean": 114.5131176870229,
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+ "latency_std": 11.639414649196416,
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+ "latency_50": 119.241188,
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+ "latency_90": 121.520665,
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+ "latency_95": 122.2199805,
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+ "latency_99": 122.8121624,
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+ "latency_999": 123.42355991
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+ "optimized": {
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+ "nb_forwards": 280,
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+ "throughput": 18.67,
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+ "latency_mean": 53.58903423571429,
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+ "latency_std": 0.2315309286545786,
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+ "latency_50": 53.5208165,
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+ "latency_90": 53.861245,
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+ "latency_95": 54.0498545,
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+ }
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+ "others": {
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+ "baseline": {
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+ "precision": 0.9358012339503085,
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+ "recall": 0.9444631437226523,
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+ "f1": 0.9401122372057961,
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+ "accuracy": 0.9882013940267124
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+ "precision": 0.9038969616908851,
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+ "recall": 0.9212386401884888,
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+ "f1": 0.912485414235706,
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+ "accuracy": 0.9842295860753086
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+ "time_benchmark_args": {
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+ "duration": 15,
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+ "warmup_runs": 5
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+ },
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+ "model_type": "distilbert"
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+ },
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+ {
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+ "model_name_or_path": "elastic/distilbert-base-uncased-finetuned-conll03-english",
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+ "task": "token-classification",
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+ "task_args": null,
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+ "dataset": {
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+ "path": "conll2003",
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+ "eval_split": "validation",
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+ "data_keys": {
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+ "primary": "tokens",
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+ "secondary": null
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+ "ref_keys": [
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+ "ner_tags"
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+ ],
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+ "name": null,
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+ "calibration_split": "train"
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+ },
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+ "quantization_approach": "static",
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+ "operators_to_quantize": [
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+ "Add",
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+ "MatMul"
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+ ],
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+ "node_exclusion": [],
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+ "aware_training": false,
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+ "per_channel": false,
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+ "calibration": {
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+ "method": "minmax",
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+ "num_calibration_samples": 100,
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+ "calibration_histogram_percentile": null,
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+ "calibration_moving_average": null,
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+ "calibration_moving_average_constant": null
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+ "framework": "onnxruntime",
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+ "opset": 11,
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+ "optimization_level": 1
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+ "transformers": "4.20.1",
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+ "optimum": "1.2.3.dev0",
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+ "optimum_hash": "6911cc6576c9fd373dfdba597e7a6b3ec37c2063"
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+ "accuracy": 0.9882013940267124
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+ "recall": 0.24335240659710536,
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