Processed data from AutoTrain data processor ([2023-02-10 11:17 ]

README.md

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+---
+language:
+- en
+task_categories:
+- text-classification
+
+---
+# AutoTrain Dataset for project: dataset-mentions
+
+## Dataset Description
+
+This dataset has been automatically processed by AutoTrain for project dataset-mentions.
+
+### Languages
+
+The BCP-47 code for the dataset's language is en.
+
+## Dataset Structure
+
+### Data Instances
+
+A sample from this dataset looks as follows:
+
+```json
+[
+  {
+    "text": " How to use  ```python from transformers import AutoTokenizer, AutoModel  tokenizer = AutoTokenizer.from_pretrained(\"Geotrend/bert-base-en-fr-zh-ja-vi-cased\") model = AutoModel.from_pretrained(\"Geotrend/bert-base-en-fr-zh-ja-vi-cased\")  ```  To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).  ",
+    "target": 0
+  },
+  {
+    "text": " Training hyperparameters  The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 24 - eval_batch_size: 24 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3  ",
+    "target": 1
+  }
+]
+```
+
+### Dataset Fields
+
+The dataset has the following fields (also called "features"):
+
+```json
+{
+  "text": "Value(dtype='string', id=None)",
+  "target": "ClassLabel(names=['dataset_mention', 'no_dataset_mention'], id=None)"
+}
+```
+
+### Dataset Splits
+
+This dataset is split into a train and validation split. The split sizes are as follow:
+
+| Split name   | Num samples         |
+| ------------ | ------------------- |
+| train        | 7428 |
+| valid        | 1858 |

processed/dataset_dict.json

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+{"splits": ["train", "valid"]}

processed/train/dataset.arrow

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+size 2939072

processed/train/dataset_info.json

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+{
+  "citation": "",
+  "description": "AutoTrain generated dataset",
+  "features": {
+    "text": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "target": {
+      "names": [
+        "dataset_mention",
+        "no_dataset_mention"
+      ],
+      "_type": "ClassLabel"
+    }
+  },
+  "homepage": "",
+  "license": "",
+  "splits": {
+    "train": {
+      "name": "train",
+      "num_bytes": 2936898,
+      "num_examples": 7428,
+      "dataset_name": null
+    }
+  }
+}

processed/train/state.json

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+{
+  "_data_files": [
+    {
+      "filename": "dataset.arrow"
+    }
+  ],
+  "_fingerprint": "0e021e6946da352a",
+  "_format_columns": [
+    "target",
+    "text"
+  ],
+  "_format_kwargs": {},
+  "_format_type": null,
+  "_indexes": {},
+  "_output_all_columns": false,
+  "_split": null
+}

processed/valid/dataset.arrow

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+oid sha256:6027215ac2c965bac4bc1af3a9063542c1a89607e3aaa636795b9c081947754f
+size 905376

processed/valid/dataset_info.json

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+{
+  "citation": "",
+  "description": "AutoTrain generated dataset",
+  "features": {
+    "text": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "target": {
+      "names": [
+        "dataset_mention",
+        "no_dataset_mention"
+      ],
+      "_type": "ClassLabel"
+    }
+  },
+  "homepage": "",
+  "license": "",
+  "splits": {
+    "valid": {
+      "name": "valid",
+      "num_bytes": 904533,
+      "num_examples": 1858,
+      "dataset_name": null
+    }
+  }
+}

processed/valid/state.json

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+{
+  "_data_files": [
+    {
+      "filename": "dataset.arrow"
+    }
+  ],
+  "_fingerprint": "01dc7a252529f9cf",
+  "_format_columns": [
+    "target",
+    "text"
+  ],
+  "_format_kwargs": {},
+  "_format_type": null,
+  "_indexes": {},
+  "_output_all_columns": false,
+  "_split": null
+}