autoevaluator
HF staff
Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluator
18fbc0b
| language: en | |
| license: mit | |
| tags: | |
| - exbert | |
| datasets: | |
| - squad_v2 | |
| thumbnail: https://thumb.tildacdn.com/tild3433-3637-4830-a533-353833613061/-/resize/720x/-/format/webp/germanquad.jpg | |
| model-index: | |
| - name: deepset/tinybert-6l-768d-squad2 | |
| results: | |
| - task: | |
| type: question-answering | |
| name: Question Answering | |
| dataset: | |
| name: squad_v2 | |
| type: squad_v2 | |
| config: squad_v2 | |
| split: validation | |
| metrics: | |
| - type: exact_match | |
| value: 73.8248 | |
| name: Exact Match | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMGFmZmFiN2E5ODZkOTkyMjQ1NTUzMmQwMjc0M2RlYzVlNmM4YTFlNzA4YzIwY2JkY2EyNDg2ZTY3OTdjZTVlZiIsInZlcnNpb24iOjF9.ZZ6c2OI3lzeNhuSWTh28j00zk-sPrqkTvdVBZv2wJc1D4YnR-xOj72haybT6MV_xeYqTg3-x9L8PsWSS20NaDw | |
| - type: f1 | |
| value: 77.1684 | |
| name: F1 | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNzAxMDk1YzI5ZjA2N2ZmMzAxNjgxYzJiNzAzYmI1ZWU5ZDRmYWY3OWJmMjlmNDcyMGE0YWY5NjNhZTk4YWY5ZSIsInZlcnNpb24iOjF9.rF3raNGUSYv5D2xzWLZztD99vwDKvWb22LG32RomrDGP6XKTbCVqZzAw5UFw93jKb0VoLApbQQ-AOGxLj3U_Cg | |
| ## Overview | |
| **Language model:** deepset/tinybert-6L-768D-squad2 | |
| **Language:** English | |
| **Training data:** SQuAD 2.0 training set x 20 augmented + SQuAD 2.0 training set without augmentation | |
| **Eval data:** SQuAD 2.0 dev set | |
| **Infrastructure**: 1x V100 GPU | |
| **Published**: Dec 8th, 2021 | |
| ## Details | |
| - haystack's intermediate layer and prediction layer distillation features were used for training (based on [TinyBERT](https://arxiv.org/pdf/1909.10351.pdf)). deepset/bert-base-uncased-squad2 was used as the teacher model and huawei-noah/TinyBERT_General_6L_768D was used as the student model. | |
| ## Hyperparameters | |
| ### Intermediate layer distillation | |
| ``` | |
| batch_size = 26 | |
| n_epochs = 5 | |
| max_seq_len = 384 | |
| learning_rate = 5e-5 | |
| lr_schedule = LinearWarmup | |
| embeds_dropout_prob = 0.1 | |
| temperature = 1 | |
| ``` | |
| ### Prediction layer distillation | |
| ``` | |
| batch_size = 26 | |
| n_epochs = 5 | |
| max_seq_len = 384 | |
| learning_rate = 3e-5 | |
| lr_schedule = LinearWarmup | |
| embeds_dropout_prob = 0.1 | |
| temperature = 1 | |
| distillation_loss_weight = 1.0 | |
| ``` | |
| ## Performance | |
| ``` | |
| "exact": 71.87736882001179 | |
| "f1": 76.36111895973675 | |
| ``` | |
| ## Authors | |
| - Timo M枚ller: `timo.moeller [at] deepset.ai` | |
| - Julian Risch: `julian.risch [at] deepset.ai` | |
| - Malte Pietsch: `malte.pietsch [at] deepset.ai` | |
| - Michel Bartels: `michel.bartels [at] deepset.ai` | |
| ## About us | |
|  | |
| We bring NLP to the industry via open source! | |
| Our focus: Industry specific language models & large scale QA systems. | |
| Some of our work: | |
| - [German BERT (aka "bert-base-german-cased")](https://deepset.ai/german-bert) | |
| - [GermanQuAD and GermanDPR datasets and models (aka "gelectra-base-germanquad", "gbert-base-germandpr")](https://deepset.ai/germanquad) | |
| - [FARM](https://github.com/deepset-ai/FARM) | |
| - [Haystack](https://github.com/deepset-ai/haystack/) | |
| Get in touch: | |
| [Twitter](https://twitter.com/deepset_ai) | [LinkedIn](https://www.linkedin.com/company/deepset-ai/) | [Discord](https://haystack.deepset.ai/community/join) | [GitHub Discussions](https://github.com/deepset-ai/haystack/discussions) | [Website](https://deepset.ai) | |
| By the way: [we're hiring!](http://www.deepset.ai/jobs) |