--- pipeline_tag: token-classification datasets: - conll2003 metrics: - precision - recall - f1 - accuracy tags: - distilbert --- **task**: `token-classification` **Backend:** `sagemaker-training` **Backend args:** `{'instance_type': 'ml.g4dn.2xlarge', 'supported_instructions': None}` **Number of evaluation samples:** `All dataset` Fixed parameters: * **model_name_or_path**: `elastic/distilbert-base-uncased-finetuned-conll03-english` * **dataset**: * **path**: `conll2003` * **eval_split**: `validation` * **data_keys**: `{'primary': 'tokens'}` * **ref_keys**: `['ner_tags']` * **calibration_split**: `train` * **quantization_approach**: `static` * **operators_to_quantize**: `['Add', 'MatMul']` * **per_channel**: `False` * **calibration**: * **method**: `minmax` * **num_calibration_samples**: `100` * **framework**: `onnxruntime` * **framework_args**: * **opset**: `11` * **optimization_level**: `1` * **aware_training**: `False` Benchmarked parameters: * **node_exclusion**: `[]`, `['layernorm', 'gelu', 'residual', 'gather', 'softmax']` # Evaluation ## Non-time metrics | node_exclusion | | precision (original) | precision (optimized) | | recall (original) | recall (optimized) | | f1 (original) | f1 (optimized) | | accuracy (original) | accuracy (optimized) | | :------------------------------------------------------: | :-: | :------------------: | :-------------------: | :-: | :---------------: | :----------------: | :-: | :-----------: | :------------: | :-: | :-----------------: | :------------------: | | `['layernorm', 'gelu', 'residual', 'gather', 'softmax']` | \| | 0.936 | 0.904 | \| | 0.944 | 0.921 | \| | 0.940 | 0.912 | \| | 0.988 | 0.984 | | `[]` | \| | 0.936 | 0.065 | \| | 0.944 | 0.243 | \| | 0.940 | 0.103 | \| | 0.988 | 0.357 | ## Time metrics Time benchmarks were run for 15 seconds per config. Below, time metrics for batch size = 4, input length = 64. | node_exclusion | | latency_mean (original, ms) | latency_mean (optimized, ms) | | throughput (original, /s) | throughput (optimized, /s) | | :------------------------------------------------------: | :-: | :-------------------------: | :--------------------------: | :-: | :-----------------------: | :------------------------: | | `['layernorm', 'gelu', 'residual', 'gather', 'softmax']` | \| | 103.46 | 53.77 | \| | 9.67 | 18.60 | | `[]` | \| | 90.62 | 65.86 | \| | 11.07 | 15.20 |