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Update token_classification notebook to use evaluate.load() instead of load_metric() from Datasets library (removed) #522

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Update token_classification notebook to use evaluate.load() instead of load_metric() from Datasets library (removed) #522

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11 changes: 6 additions & 5 deletions examples/token_classification.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,7 @@
},
"outputs": [],
"source": [
"#! pip install datasets transformers seqeval"
"#! pip install datasets transformers seqeval evaluate"
]
},
{
Expand Down Expand Up @@ -171,7 +171,7 @@
"id": "W7QYTpxXIrIl"
},
"source": [
"We will use the [🤗 Datasets](https://github.com/huggingface/datasets) library to download the data and get the metric we need to use for evaluation (to compare our model to the benchmark). This can be easily done with the functions `load_dataset` and `load_metric`. "
"We will use the [🤗 Datasets](https://github.com/huggingface/datasets) library to download the data. This can be easily done with the `load_dataset` function. To get the metric we need to use for evaluation (to compare our model to the benchmark), we will use the [🤗 Evaluate](https://github.com/huggingface/evaluate) library."
]
},
{
Expand All @@ -182,7 +182,8 @@
},
"outputs": [],
"source": [
"from datasets import load_dataset, load_metric"
"from datasets import load_dataset\n",
"import evaluate"
]
},
{
Expand Down Expand Up @@ -1096,7 +1097,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"The last thing to define for our `Trainer` is how to compute the metrics from the predictions. Here we will load the [`seqeval`](https://github.com/chakki-works/seqeval) metric (which is commonly used to evaluate results on the CONLL dataset) via the Datasets library."
"The last thing to define for our `Trainer` is how to compute the metrics from the predictions. Here we will load the [`seqeval`](https://github.com/chakki-works/seqeval) metric (which is commonly used to evaluate results on the CONLL dataset) via the Evaluate library."
]
},
{
Expand All @@ -1105,7 +1106,7 @@
"metadata": {},
"outputs": [],
"source": [
"metric = load_metric(\"seqeval\")"
"metric = evaluate.load(\"seqeval\")"
]
},
{
Expand Down