| 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 | | |