[model_card] Keep the model card readable even with many datasets (#…

…3088)

* Keep the model card readable even with many datasets

* Avoid 2 consecutive empty lines in model card

sentence_transformers/model_card_template.md

@@ -6,7 +6,7 @@
 
 # {{ model_name if model_name else "Sentence Transformer model" }}
 
-This is a [sentence-transformers](https://www.SBERT.net) model{% if base_model %} finetuned from [{{ base_model }}](https://huggingface.co/{{ base_model }}){% else %} trained{% endif %}{% if train_datasets | selectattr("name") | list %} on the {% for dataset in (train_datasets | selectattr("name")) %}{% if dataset.id %}[{{ dataset.name if dataset.name else dataset.id }}](https://huggingface.co/datasets/{{ dataset.id }}){% else %}{{ dataset.name }}{% endif %}{% if not loop.last %}{% if loop.index == (train_datasets | selectattr("name") | list | length - 1) %} and {% else %}, {% endif %}{% endif %}{% endfor %} dataset{{"s" if train_datasets | selectattr("name") | list | length > 1 else ""}}{% endif %}. It maps sentences & paragraphs to a {{ output_dimensionality }}-dimensional dense vector space and can be used for {{ task_name }}.
+This is a [sentence-transformers](https://www.SBERT.net) model{% if base_model %} finetuned from [{{ base_model }}](https://huggingface.co/{{ base_model }}){% else %} trained{% endif %}{% if train_datasets | selectattr("name") | list %} on {% if train_datasets | selectattr("name") | map(attribute="name") | join(", ") | length > 200 %}{{ train_datasets | length }}{% else %}the {% for dataset in (train_datasets | selectattr("name")) %}{% if dataset.id %}[{{ dataset.name if dataset.name else dataset.id }}](https://huggingface.co/datasets/{{ dataset.id }}){% else %}{{ dataset.name }}{% endif %}{% if not loop.last %}{% if loop.index == (train_datasets | selectattr("name") | list | length - 1) %} and {% else %}, {% endif %}{% endif %}{% endfor %}{% endif %} dataset{{"s" if train_datasets | selectattr("name") | list | length > 1 else ""}}{% endif %}. It maps sentences & paragraphs to a {{ output_dimensionality }}-dimensional dense vector space and can be used for {{ task_name }}.
 
 ## Model Details
 
@@ -156,18 +156,20 @@ You can finetune this model on your own dataset.
 ## Training Details
 {% for dataset_type, dataset_list in [("training", train_datasets), ("evaluation", eval_datasets)] %}{% if dataset_list %}
 ### {{ dataset_type.title() }} Dataset{{"s" if dataset_list | length > 1 else ""}}
-{% for dataset in dataset_list %}
+{% for dataset in dataset_list %}{% if dataset_list | length > 3 %}<details><summary>{{ dataset['name'] or 'Unnamed Dataset' }}</summary>
+{% endif %}
 #### {{ dataset['name'] or 'Unnamed Dataset' }}
-
-{% if dataset['name'] %}* Dataset: {% if 'id' in dataset %}[{{ dataset['name'] }}](https://huggingface.co/datasets/{{ dataset['id'] }}){% else %}{{ dataset['name'] }}{% endif %}
+{% if dataset['name'] %}
+* Dataset: {% if 'id' in dataset %}[{{ dataset['name'] }}](https://huggingface.co/datasets/{{ dataset['id'] }}){% else %}{{ dataset['name'] }}{% endif %}
 {%- if 'revision' in dataset and 'id' in dataset %} at [{{ dataset['revision'][:7] }}](https://huggingface.co/datasets/{{ dataset['id'] }}/tree/{{ dataset['revision'] }}){% endif %}{% endif %}
 {% if dataset['size'] %}* Size: {{ "{:,}".format(dataset['size']) }} {{ dataset_type }} samples
 {% endif %}* Columns: {% if dataset['columns'] | length == 1 %}{{ dataset['columns'][0] }}{% elif dataset['columns'] | length == 2 %}{{ dataset['columns'][0] }} and {{ dataset['columns'][1] }}{% else %}{{ dataset['columns'][:-1] | join(', ') }}, and {{ dataset['columns'][-1] }}{% endif %}
 {% if dataset['stats_table'] %}* Approximate statistics based on the first {{ [dataset['size'], 1000] | min }} samples:
 {{ dataset['stats_table'] }}{% endif %}{% if dataset['examples_table'] %}* Samples:
 {{ dataset['examples_table'] }}{% endif %}* Loss: {% if dataset["loss"]["fullname"].startswith("sentence_transformers.") %}[<code>{{ dataset["loss"]["fullname"].split(".")[-1] }}</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#{{ dataset["loss"]["fullname"].split(".")[-1].lower() }}){% else %}<code>{{ dataset["loss"]["fullname"] }}</code>{% endif %}{% if "config_code" in dataset["loss"] %} with these parameters:
 {{ dataset["loss"]["config_code"] }}{% endif %}
-{% endfor %}{% endif %}{% endfor -%}
+{% if dataset_list | length > 3 %}</details>
+{% endif %}{% endfor %}{% endif %}{% endfor -%}
 
 {% if all_hyperparameters %}
 ### Training Hyperparameters

tests/test_model_card.py

@@ -0,0 +1,111 @@
+from __future__ import annotations
+
+import pytest
+from datasets import Dataset, DatasetDict
+
+from sentence_transformers import SentenceTransformer, SentenceTransformerTrainer
+from sentence_transformers.model_card import generate_model_card
+
+
+@pytest.fixture(scope="session")
+def dummy_dataset():
+    """
+    Dummy dataset for testing purposes. The dataset looks as follows:
+    {
+        "anchor": ["anchor 1", "anchor 2", ..., "anchor 10"],
+        "positive": ["positive 1", "positive 2", ..., "positive 10"],
+        "negative": ["negative 1", "negative 2", ..., "negative 10"],
+    }
+    """
+    return Dataset.from_dict(
+        {
+            "anchor": [f"anchor {i}" for i in range(1, 11)],
+            "positive": [f"positive {i}" for i in range(1, 11)],
+            "negative": [f"negative {i}" for i in range(1, 11)],
+        }
+    )
+
+
+@pytest.mark.parametrize(
+    ("num_datasets", "expected_substrings"),
+    [
+        # 0 actually refers to just a single dataset
+        (
+            0,
+            [
+                "This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers-testing/stsb-bert-tiny-safetensors](https://huggingface.co/sentence-transformers-testing/stsb-bert-tiny-safetensors).",
+                "**Maximum Sequence Length:** 512 tokens",
+                "**Output Dimensionality:** 128 dimensions",
+                "**Similarity Function:** Cosine Similarity",
+                "#### Unnamed Dataset",
+                " | <code>anchor 1</code> | <code>positive 1</code> | <code>negative 1</code> |",
+                "* Loss: [<code>CoSENTLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosentloss) with these parameters:",
+            ],
+        ),
+        (
+            1,
+            [
+                "This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers-testing/stsb-bert-tiny-safetensors](https://huggingface.co/sentence-transformers-testing/stsb-bert-tiny-safetensors) on the train_0 dataset.",
+                "#### train_0",
+            ],
+        ),
+        (
+            2,
+            [
+                "This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers-testing/stsb-bert-tiny-safetensors](https://huggingface.co/sentence-transformers-testing/stsb-bert-tiny-safetensors) on the train_0 and train_1 datasets.",
+                "#### train_0",
+                "#### train_1",
+            ],
+        ),
+        (
+            10,
+            [
+                "This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers-testing/stsb-bert-tiny-safetensors](https://huggingface.co/sentence-transformers-testing/stsb-bert-tiny-safetensors) on the train_0, train_1, train_2, train_3, train_4, train_5, train_6, train_7, train_8 and train_9 datasets.",
+                "<details><summary>train_0</summary>",  # We start using <details><summary> if we have more than 3 datasets
+                "#### train_0",
+                "</details>\n<details><summary>train_9</summary>",
+                "#### train_9",
+            ],
+        ),
+        # We start using "50 datasets" when the ", "-joined dataset name exceed 200 characters
+        (
+            50,
+            [
+                "This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers-testing/stsb-bert-tiny-safetensors](https://huggingface.co/sentence-transformers-testing/stsb-bert-tiny-safetensors) on 50 datasets.",
+                "<details><summary>train_0</summary>",
+                "#### train_0",
+                "</details>\n<details><summary>train_49</summary>",
+                "#### train_49",
+            ],
+        ),
+    ],
+)
+def test_model_card_base(
+    stsb_bert_tiny_model: SentenceTransformer,
+    dummy_dataset: Dataset,
+    num_datasets: int,
+    expected_substrings: list[str],
+) -> None:
+    model = stsb_bert_tiny_model
+
+    train_dataset = dummy_dataset
+    if num_datasets:
+        train_dataset = DatasetDict({f"train_{i}": train_dataset for i in range(num_datasets)})
+
+    # This adds data to model.model_card_data
+    SentenceTransformerTrainer(
+        model,
+        train_dataset=train_dataset,
+    )
+
+    model_card = generate_model_card(model)
+
+    # For debugging purposes, we save the model card to a file
+    # with open(f"test_model_card_{num_datasets}.md", "w", encoding="utf8") as f:
+    #     f.write(model_card)
+
+    for substring in expected_substrings:
+        assert substring in model_card
+
+    # We don't want to have two consecutive empty lines anywhere
+    assert "\n\n\n" not in model_card