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21
README.md
21
README.md
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@ -2,10 +2,10 @@
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language: en
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language: en
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tags:
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tags:
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- tapas
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- tapas
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- question-answering
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- table-question-answering
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license: apache-2.0
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license: apache-2.0
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datasets:
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datasets:
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- sqa
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- msr_sqa
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---
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---
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# TAPAS base model fine-tuned on Sequential Question Answering (SQA)
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# TAPAS base model fine-tuned on Sequential Question Answering (SQA)
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@ -19,6 +19,23 @@ The other (non-default) version which can be used is:
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Disclaimer: The team releasing TAPAS did not write a model card for this model so this model card has been written by
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Disclaimer: The team releasing TAPAS did not write a model card for this model so this model card has been written by
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the Hugging Face team and contributors.
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the Hugging Face team and contributors.
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## Results on SQA - Dev Accuracy
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Size | Reset | Dev Accuracy | Link
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-------- | --------| -------- | ----
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LARGE | noreset | 0.7223 | [tapas-large-finetuned-sqa (absolute pos embeddings)](https://huggingface.co/google/tapas-large-finetuned-sqa/tree/no_reset)
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LARGE | reset | 0.7289 | [tapas-large-finetuned-sqa](https://huggingface.co/google/tapas-large-finetuned-sqa/tree/main)
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**BASE** | **noreset** | **0.6737** | [tapas-base-finetuned-sqa (absolute pos embeddings)](https://huggingface.co/google/tapas-base-finetuned-sqa/tree/no_reset)
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**BASE** | **reset** | **0.6874** | [tapas-base-finetuned-sqa](https://huggingface.co/google/tapas-base-finetuned-sqa/tree/main)
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MEDIUM | noreset | 0.6464 | [tapas-medium-finetuned-sqa (absolute pos embeddings)](https://huggingface.co/google/tapas-medium-finetuned-sqa/tree/no_reset)
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MEDIUM | reset | 0.6561 | [tapas-medium-finetuned-sqa](https://huggingface.co/google/tapas-medium-finetuned-sqa/tree/main)
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SMALL | noreset | 0.5876 | [tapas-small-finetuned-sqa (absolute pos embeddings)](https://huggingface.co/google/tapas-small-finetuned-sqa/tree/no_reset)
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SMALL | reset | 0.6155 | [tapas-small-finetuned-sqa](https://huggingface.co/google/tapas-small-finetuned-sqa/tree/main)
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MINI | noreset | 0.4574 | [tapas-mini-finetuned-sqa (absolute pos embeddings)](https://huggingface.co/google/tapas-mini-finetuned-sqa/tree/no_reset)
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MINI | reset | 0.5148 | [tapas-mini-finetuned-sqa](https://huggingface.co/google/tapas-mini-finetuned-sqa/tree/main))
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TINY | noreset | 0.2004 | [tapas-tiny-finetuned-sqa (absolute pos embeddings)](https://huggingface.co/google/tapas-tiny-finetuned-sqa/tree/no_reset)
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TINY | reset | 0.2375 | [tapas-tiny-finetuned-sqa](https://huggingface.co/google/tapas-tiny-finetuned-sqa/tree/main)
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## Model description
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## Model description
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TAPAS is a BERT-like transformers model pretrained on a large corpus of English data from Wikipedia in a self-supervised fashion.
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TAPAS is a BERT-like transformers model pretrained on a large corpus of English data from Wikipedia in a self-supervised fashion.
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122
config.json
122
config.json
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@ -1,59 +1,63 @@
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{
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{
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"aggregation_loss_weight": 1.0,
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"_name_or_path": "google/tapas-base-finetuned-sqa",
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"aggregation_temperature": 1.0,
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"aggregation_labels": null,
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"allow_empty_column_selection": false,
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"aggregation_loss_weight": 1.0,
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"answer_loss_cutoff": null,
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"aggregation_temperature": 1.0,
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"answer_loss_importance": 1.0,
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"allow_empty_column_selection": false,
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"architectures": [
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"answer_loss_cutoff": null,
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"TapasForQuestionAnswering"
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"answer_loss_importance": 1.0,
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],
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"architectures": [
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"attention_probs_dropout_prob": 0.1,
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"TapasForQuestionAnswering"
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"average_approximation_function": "ratio",
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],
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"average_logits_per_cell": false,
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"attention_probs_dropout_prob": 0.1,
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"cell_selection_preference": null,
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"average_approximation_function": "ratio",
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"disable_per_token_loss": false,
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"average_logits_per_cell": false,
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"gradient_checkpointing": false,
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"cell_selection_preference": null,
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"hidden_act": "gelu",
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"disable_per_token_loss": false,
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"hidden_dropout_prob": 0.1,
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"gradient_checkpointing": false,
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"hidden_size": 768,
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"hidden_act": "gelu",
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"huber_loss_delta": null,
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"hidden_dropout_prob": 0.1,
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"init_cell_selection_weights_to_zero": false,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"huber_loss_delta": null,
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"intermediate_size": 3072,
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"init_cell_selection_weights_to_zero": false,
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"layer_norm_eps": 1e-12,
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"initializer_range": 0.02,
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"max_num_columns": 32,
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"intermediate_size": 3072,
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"max_num_rows": 64,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 1024,
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"max_num_columns": 32,
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"model_type": "tapas",
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"max_num_rows": 64,
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"num_aggregation_labels": 0,
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"max_position_embeddings": 1024,
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"num_attention_heads": 12,
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"model_type": "tapas",
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"num_hidden_layers": 12,
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"no_aggregation_label_index": null,
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"pad_token_id": 0,
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"num_aggregation_labels": 0,
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"positive_label_weight": 10.0,
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"num_attention_heads": 12,
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"reset_position_index_per_cell": true,
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"num_hidden_layers": 12,
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"select_one_column": true,
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"pad_token_id": 0,
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"softmax_temperature": 1.0,
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"positive_label_weight": 10.0,
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"type_vocab_size": [
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"reset_position_index_per_cell": true,
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3,
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"select_one_column": true,
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256,
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"softmax_temperature": 1.0,
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256,
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"transformers_version": "4.13.0.dev0",
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2,
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"type_vocab_size": [
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256,
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3,
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256,
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256,
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10
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256,
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],
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2,
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"type_vocab_sizes": [
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256,
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3,
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256,
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256,
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10
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256,
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],
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2,
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"type_vocab_sizes": [
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256,
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3,
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256,
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256,
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10
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256,
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],
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2,
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"use_answer_as_supervision": null,
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256,
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"use_gumbel_for_aggregation": false,
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256,
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"use_gumbel_for_cells": false,
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10
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"use_normalized_answer_loss": false,
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],
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"vocab_size": 30522
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"use_answer_as_supervision": null,
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}
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"use_gumbel_for_aggregation": false,
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"use_gumbel_for_cells": false,
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"use_normalized_answer_loss": false,
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"vocab_size": 30522
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}
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