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aj280192 authored Mar 29, 2022
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Expand Up @@ -19,7 +19,7 @@ arXiv pre-print available here: https://arxiv.org/abs/2108.13961

### With pip

[![PyPI](https://img.shields.io/pypi/v/thermostat-datasets?style=flat-square)](https://pypi.org/project/thermostat-datasets/)]
[![PyPI](https://img.shields.io/pypi/v/thermostat-datasets?style=flat-square)](https://pypi.org/project/thermostat-datasets/)

```bash
pip install thermostat-datasets
Expand Down Expand Up @@ -144,8 +144,8 @@ Layer Integrated Gradients (`lig`) | [`.attr.LayerIntegratedGradients`](https://
LIME (`lime`) | [`.attr.LimeBase`](https://captum.ai/api/lime.html) | # samples = 25, <br>mask prob = 0.3
Occlusion (`occ`) | [`.attr.Occlusion`](https://captum.ai/api/occlusion.html) | sliding window = 3
Shapley Value Sampling (`svs`) | [`.attr.ShapleyValueSampling`](https://captum.ai/api/shapley_value_sampling.html) | # samples = 25
Layer DeepLiftShap ('lds') | [`.attr.LayerDeepLiftShap`](https://captum.ai/api/layer.html#layer-deepliftshap) |
Layer GradientShap ('lgs') | [`attr.LayerGradientShap`](https://captum.ai/api/layer.html#layer-gradientshap) | # samples = 5
Layer DeepLiftShap (`lds`) | [`.attr.LayerDeepLiftShap`](https://captum.ai/api/layer.html#layer-deepliftshap) |
Layer GradientShap (`lgs`) | [`.attr.LayerGradientShap`](https://captum.ai/api/layer.html#layer-gradientshap) | # samples = 5



Expand All @@ -164,7 +164,7 @@ Layer GradientShap ('lgs') | [`attr.LayerGradientShap`](https://captum.ai/api/la
[`imdb`](https://huggingface.co/datasets/viewer/?dataset=imdb) is a sentiment analysis dataset with 2 classes (`pos` and `neg`). The available split is the `test` subset containing 25k examples.
Example configuration: `imdb-xlnet-lig`

Name | 🤗 | `lgxa` | `lig` | `lime` | `occ` | `svs` | 'lds' | 'lgs'
Name | 🤗 | `lgxa` | `lig` | `lime` | `occ` | `svs` | `lds` | `lgs`
--- | --- | --- | --- | --- | --- | --- | --- | ---
ALBERT (`albert`) | [`textattack/albert-base-v2-imdb`](https://huggingface.co/textattack/albert-base-v2-imdb) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅
BERT (`bert`) | [`textattack/bert-base-uncased-imdb`](https://huggingface.co/textattack/bert-base-uncased-imdb) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅
Expand All @@ -178,7 +178,7 @@ XLNet (`xlnet`) | [`textattack/xlnet-base-cased-imdb`](https://huggingface.co/te
[`multi_nli`](https://huggingface.co/datasets/viewer/?dataset=multi_nli) is a textual entailment dataset. The available split is the `validation_matched` subset containing 9815 examples.
Example configuration: `multi_nli-roberta-lime`

Name | 🤗 | `lgxa` | `lig` | `lime` | `occ` | `svs` | 'lds' | 'lgs'
Name | 🤗 | `lgxa` | `lig` | `lime` | `occ` | `svs` | `lds` | `lgs`
--- | --- | --- | --- | --- | --- | --- | --- | ---
ALBERT (`albert`) | [`prajjwal1/albert-base-v2-mnli`](https://huggingface.co/prajjwal1/albert-base-v2-mnli) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅
BERT (`bert`) | [`textattack/bert-base-uncased-MNLI`](https://huggingface.co/textattack/bert-base-uncased-MNLI) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅
Expand All @@ -192,7 +192,7 @@ XLNet (`xlnet`) | [`textattack/xlnet-base-cased-MNLI`](https://huggingface.co/te
[`xnli`](https://huggingface.co/datasets/viewer/?dataset=xnli) is a textual entailment dataset. It provides the test set of MultiNLI through the "en" configuration. The fine-tuned models used here are the same as the MultiNLI ones. The available split is the `test` subset containing 5010 examples.
Example configuration: `xnli-roberta-lime`

Name | 🤗 | `lgxa` | `lig` | `lime` | `occ` | `svs` | 'lds' | 'lgs'
Name | 🤗 | `lgxa` | `lig` | `lime` | `occ` | `svs` | `lds` | `lgs`
--- | --- | --- | --- | --- | --- | --- | --- | ---
ALBERT (`albert`) | [`prajjwal1/albert-base-v2-mnli`](https://huggingface.co/prajjwal1/albert-base-v2-mnli) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅
BERT (`bert`) | [`textattack/bert-base-uncased-MNLI`](https://huggingface.co/textattack/bert-base-uncased-MNLI) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅
Expand All @@ -206,7 +206,7 @@ XLNet (`xlnet`) | [`textattack/xlnet-base-cased-MNLI`](https://huggingface.co/te
[`ag_news`](https://huggingface.co/datasets/viewer/?dataset=ag_news) is a news topic classification dataset. The available split is the `test` subset containing 7600 examples.
Example configuration: `ag_news-albert-svs`

Name | 🤗 | `lgxa` | `lig` | `lime` | `occ` | `svs` | 'lds' | 'lgs'
Name | 🤗 | `lgxa` | `lig` | `lime` | `occ` | `svs` | `lds` | `lgs`
--- | --- | --- | --- | --- | --- | --- | --- | ---
ALBERT (`albert`) | [`textattack/albert-base-v2-ag-news`](https://huggingface.co/textattack/albert-base-v2-ag-news) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅
BERT (`bert`) | [`textattack/bert-base-uncased-ag-news`](https://huggingface.co/textattack/bert-base-uncased-ag-news) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅
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