Initial commit

README.md

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+---
+tags:
+- bert
+- mobilebert
+- oBERT
+language: en
+datasets: squad
+---
+# mobilebert-uncased-finetuned-squadv1
+
+This model is a finetuned version of the [mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased/tree/main) model on the SQuADv1 task.
+
+It is produced as part of the work on the paper [The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models](https://arxiv.org/abs/2203.07259).
+
+SQuADv1 dev-set:
+```
+EM = 83.96
+F1 = 90.90
+```
+
+Code: [https://github.com/neuralmagic/sparseml/tree/main/research/optimal_BERT_surgeon_oBERT](https://github.com/neuralmagic/sparseml/tree/main/research/optimal_BERT_surgeon_oBERT)
+
+If you find the model useful, please consider citing our work.
+
+## Citation info
+```bibtex
+@article{kurtic2022optimal,
+  title={The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models},
+  author={Kurtic, Eldar and Campos, Daniel and Nguyen, Tuan and Frantar, Elias and Kurtz, Mark and Fineran, Benjamin and Goin, Michael and Alistarh, Dan},
+  journal={arXiv preprint arXiv:2203.07259},
+  year={2022}
+}
+```

config.json

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+{
+  "_name_or_path": "neuralmagic/mobilebert-uncased-finetuned-squadv1",
+  "architectures": [
+    "MobileBertForQuestionAnswering"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "classifier_activation": false,
+  "classifier_dropout": null,
+  "embedding_size": 128,
+  "hidden_act": "relu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 512,
+  "initializer_range": 0.02,
+  "intermediate_size": 512,
+  "intra_bottleneck_size": 128,
+  "key_query_shared_bottleneck": true,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "mobilebert",
+  "normalization_type": "no_norm",
+  "num_attention_heads": 4,
+  "num_feedforward_networks": 4,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "torch_dtype": "float32",
+  "transformers_version": "4.18.0.dev0",
+  "trigram_input": true,
+  "true_hidden_size": 128,
+  "type_vocab_size": 2,
+  "use_bottleneck": true,
+  "use_bottleneck_attention": false,
+  "vocab_size": 30522
+}

eval_results.json

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+{
+    "epoch": 5.0,
+    "eval_exact_match": 83.96404919583728,
+    "eval_f1": 90.90359324656357,
+    "eval_samples": 10784
+}

pytorch_model.bin

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+size 98801471

special_tokens_map.json

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+{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

tokenizer_config.json

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+{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "integrations/huggingface-transformers/output_dir/teachers/squad/bert_large_uncased_FP32", "tokenizer_class": "BertTokenizer"}