Add adapter gpt2_nli_rte_houlsby version 1
Browse files- README.md +54 -0
- adapter_config.json +41 -0
- head_config.json +21 -0
- pytorch_adapter.bin +3 -0
- pytorch_model_head.bin +3 -0
README.md
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---
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tags:
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- gpt2
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- adapterhub:nli/rte
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- adapter-transformers
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- text-classification
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license: "apache-2.0"
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---
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# Adapter `gpt2_nli_rte_houlsby` for gpt2
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Adapter for gpt2 in Houlsby architecture trained on the RTE dataset for 10 epochs with a learning rate of 1e-4.
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**This adapter was created for usage with the [Adapters](https://github.com/Adapter-Hub/adapters) library.**
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## Usage
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First, install `adapters`:
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```
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pip install -U adapters
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```
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Now, the adapter can be loaded and activated like this:
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```python
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from adapters import AutoAdapterModel
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model = AutoAdapterModel.from_pretrained("gpt2")
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adapter_name = model.load_adapter("AdapterHub/gpt2_nli_rte_houlsby")
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model.set_active_adapters(adapter_name)
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```
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## Architecture & Training
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- Adapter architecture: houlsby
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- Prediction head: classification
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- Dataset: [RTE](https://aclweb.org/aclwiki/Recognizing_Textual_Entailment)
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## Author Information
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- Author name(s): Hannah Sterz
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- Author email: [email protected]
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- Author links: [Twitter](https://twitter.com/@h_sterz)
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## Citation
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```bibtex
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```
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*This adapter has been auto-imported from https://github.com/Adapter-Hub/Hub/blob/master/adapters/ukp/gpt2_nli_rte_houlsby.yaml*.
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adapter_config.json
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{
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"config": {
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"adapter_residual_before_ln": false,
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"cross_adapter": false,
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"dropout": 0.0,
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"factorized_phm_W": true,
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"factorized_phm_rule": false,
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"hypercomplex_nonlinearity": "glorot-uniform",
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"init_weights": "bert",
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"inv_adapter": null,
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"inv_adapter_reduction_factor": null,
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"is_parallel": false,
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"learn_phm": true,
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"leave_out": [],
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"ln_after": false,
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"ln_before": false,
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"mh_adapter": true,
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"non_linearity": "swish",
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"original_ln_after": true,
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"original_ln_before": false,
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"output_adapter": true,
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"phm_bias": true,
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"phm_c_init": "normal",
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"phm_dim": 4,
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"phm_init_range": 0.0001,
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"phm_layer": false,
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"phm_rank": 1,
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"reduction_factor": 16,
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"residual_before_ln": true,
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"scaling": 1.0,
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"shared_W_phm": false,
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"shared_phm_rule": true,
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"use_gating": false
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},
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"hidden_size": 768,
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"model_class": "GPT2AdapterModel",
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"model_name": "gpt2",
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"model_type": "gpt2",
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"name": "rte",
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"version": "0.2.0"
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}
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head_config.json
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{
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"config": {
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"activation_function": null,
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"bias": false,
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"dropout_prob": null,
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"head_type": "classification",
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"label2id": {
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"entailment": 0,
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"not_entailment": 1
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},
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"layers": 1,
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"num_labels": 2,
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"use_pooler": false
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},
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"hidden_size": 768,
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"model_class": "GPT2AdapterModel",
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"model_name": "gpt2",
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"model_type": "gpt2",
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"name": "rte",
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"version": "0.2.0"
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}
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pytorch_adapter.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:93573a5fae1c00e5d0202174f821f6492f97c29ab16af84235bf4201e8128b9a
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size 7189718
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pytorch_model_head.bin
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version https://git-lfs.github.com/spec/v1
|
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oid sha256:4e4cf718b4883231df8a40a9e1d284b1dee38e03ba6c06758152a9ef3195a7d2
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size 7443
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