Add new SentenceTransformer model

1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+  "word_embedding_dimension": 1024,
+  "pooling_mode_cls_token": true,
+  "pooling_mode_mean_tokens": false,
+  "pooling_mode_max_tokens": false,
+  "pooling_mode_mean_sqrt_len_tokens": false,
+  "pooling_mode_weightedmean_tokens": false,
+  "pooling_mode_lasttoken": false,
+  "include_prompt": true
+}

README.md

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+---
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- generated_from_trainer
+- dataset_size:410
+- loss:MatryoshkaLoss
+- loss:MultipleNegativesRankingLoss
+base_model: Snowflake/snowflake-arctic-embed-l
+widget:
+- source_sentence: How did the LORD respond to Sarah's laughter and doubt about bearing
+    a child?
+  sentences:
+  - '"Stay here with the donkey; the boy and I will go over there; we will worship,
+    and then we will come back to you." [22:6] Abraham took the wood of the burnt
+    offering and laid it on his son Isaac, and he himself carried the fire and the
+    knife. So the two of them walked on together. [22:7] Isaac said to his father
+    Abraham, "Father!" And he said, "Here I am, my son." He said, "The fire and the
+    wood are here, but where is the lamb for a burnt offering?" [22:8] Abraham said,
+    "God himself will provide the lamb for a burnt offering, my son." So the two of
+    them walked on together. [22:9] When they came to the place that God had shown
+    him, Abraham built an altar there and laid the wood in order. He bound his son
+    Isaac, and laid him on the altar, on'
+  - you in due season, and your wife Sarah shall have a son." And Sarah was listening
+    at the tent entrance behind him. [18:11] Now Abraham and Sarah were old, advanced
+    in age; it had ceased to be with Sarah after the manner of women. [18:12] So Sarah
+    laughed to herself, saying, "After I have grown old, and my husband is old, shall
+    I have pleasure?" [18:13] The LORD said to Abraham, "Why did Sarah laugh, and
+    say, 'Shall I indeed bear a child, now that I am old?' [18:14] Is anything too
+    wonderful for the LORD? At the set time I will return to you, in due season, and
+    Sarah shall have a son." [18:15] But Sarah denied, saying, "I did not laugh";
+    for she was afraid. He said, "Oh yes, you did laugh." [18:16] Then the men set
+    out from there, and they
+  - face; perhaps he will accept me." [32:21] So the present passed on ahead of him;
+    and he himself spent that night in the camp. [32:22] The same night he got up
+    and took his two wives, his two maids, and his eleven children, and crossed the
+    ford of the Jabbok. [32:23] He took them and sent them across the stream, and
+    likewise everything that he had. [32:24] Jacob was left alone; and a man wrestled
+    with him until daybreak. [32:25] When the man saw that he did not prevail against
+    Jacob, he struck him on the hip socket; and Jacob's hip was put out of joint as
+    he wrestled with him. [32:26] Then he said, "Let me go, for the day is breaking."
+    But Jacob said, "I will not let you go, unless you bless me." [32:27] So he said
+    to him, "What is your
+- source_sentence: What land does God promise to give to Abraham and his offspring?
+  sentences:
+  - for I have made you the ancestor of a multitude of nations. [17:6] I will make
+    you exceedingly fruitful; and I will make nations of you, and kings shall come
+    from you. [17:7] I will establish my covenant between me and you, and your offspring
+    after you throughout their generations, for an everlasting covenant, to be God
+    to you and to your offspring after you. [17:8] And I will give to you, and to
+    your offspring after you, the land where you are now an alien, all the land of
+    Canaan, for a perpetual holding; and I will be their God." [17:9] God said to
+    Abraham, "As for you, you shall keep my covenant, you and your offspring after
+    you throughout their generations. [17:10] This is my covenant, which you shall
+    keep, between me and you and your
+  - and his mother prepared savory food, such as his father loved. [27:15] Then Rebekah
+    took the best garments of her elder son Esau, which were with her in the house,
+    and put them on her younger son Jacob; [27:16] and she put the skins of the kids
+    on his hands and on the smooth part of his neck. [27:17] Then she handed the savory
+    food, and the bread that she had prepared, to her son Jacob. [27:18] So he went
+    in to his father, and said, "My father"; and he said, "Here I am; who are you,
+    my son?" [27:19] Jacob said to his father, "I am Esau your firstborn. I have done
+    as you told me; now sit up and eat of my game, so that you may bless me." [27:20]
+    But Isaac said to his son, "How is it that you have found it so quickly, my son?"
+    He answered,
+  - you for a burying place, so that I may bury my dead out of my sight." [23:5] The
+    Hittites answered Abraham, [23:6] "Hear us, my lord; you are a mighty prince among
+    us. Bury your dead in the choicest of our burial places; none of us will withhold
+    from you any burial ground for burying your dead." [23:7] Abraham rose and bowed
+    to the Hittites, the people of the land. [23:8] He said to them, "If you are willing
+    that I should bury my dead out of my sight, hear me, and entreat for me Ephron
+    son of Zohar, [23:9] so that he may give me the cave of Machpelah, which he owns;
+    it is at the end of his field. For the full price let him give it to me in your
+    presence as a possession for a burying place." [23:10] Now Ephron was sitting
+    among the
+- source_sentence: At what age did Enosh become the father of Kenan?
+  sentences:
+  - of Egypt to the great river, the river Euphrates, [15:19] the land of the Kenites,
+    the Kenizzites, the Kadmonites, [15:20] the Hittites, the Perizzites, the Rephaim,
+    [15:21] the Amorites, the Canaanites, the Girgashites, and the Jebusites.". Chapter
+    16 [16:1] Now Sarai, Abram's wife, bore him no children. She had an Egyptian slave-girl
+    whose name was Hagar, [16:2] and Sarai said to Abram, "You see that the LORD has
+    prevented me from bearing children; go in to my slave-girl; it may be that I shall
+    obtain children by her." And Abram listened to the voice of Sarai. [16:3] So,
+    after Abram had lived ten years in the land of Canaan, Sarai, Abram's wife, took
+    Hagar the Egyptian, her slave-girl, and gave her to her husband Abram as a wife.
+    [16:4]
+  - to his image, and named him Seth. [5:4] The days of Adam after he became the father
+    of Seth were eight hundred years; and he had other sons and daughters. [5:5] Thus
+    all the days that Adam lived were nine hundred thirty years; and he died. [5:6]
+    When Seth had lived one hundred five years, he became the father of Enosh. [5:7]
+    Seth lived after the birth of Enosh eight hundred seven years, and had other sons
+    and daughters. [5:8] Thus all the days of Seth were nine hundred twelve years;
+    and he died. [5:9] When Enosh had lived ninety years, he became the father of
+    Kenan. [5:10] Enosh lived after the birth of Kenan eight hundred fifteen years,
+    and had other sons and daughters. [5:11] Thus all the days of Enosh were nine
+    hundred five years; and
+  - said, "Come, let us build ourselves a city, and a tower with its top in the heavens,
+    and let us make a name for ourselves; otherwise we shall be scattered abroad upon
+    the face of the whole earth." [11:5] The LORD came down to see the city and the
+    tower, which mortals had built. [11:6] And the LORD said, "Look, they are one
+    people, and they have all one language; and this is only the beginning of what
+    they will do; nothing that they propose to do will now be impossible for them.
+    [11:7] Come, let us go down, and confuse their language there, so that they will
+    not understand one another's speech." [11:8] So the LORD scattered them abroad
+    from there over the face of all the earth, and they left off building the city.
+    [11:9] Therefore it was
+- source_sentence: How did the angels assist Lot and his family in escaping the city?
+  sentences:
+  - has become great before the LORD, and the LORD has sent us to destroy it." [19:14]
+    So Lot went out and said to his sons-in-law, who were to marry his daughters,
+    "Up, get out of this place; for the LORD is about to destroy the city." But he
+    seemed to his sons-in-law to be jesting. [19:15] When morning dawned, the angels
+    urged Lot, saying, "Get up, take your wife and your two daughters who are here,
+    or else you will be consumed in the punishment of the city." [19:16] But he lingered;
+    so the men seized him and his wife and his two daughters by the hand, the LORD
+    being merciful to him, and they brought him out and left him outside the city.
+    [19:17] When they had brought them outside, they said, "Flee for your life; do
+    not look back or stop
+  - five years; and he died. [5:12] When Kenan had lived seventy years, he became
+    the father of Mahalalel. [5:13] Kenan lived after the birth of Mahalalel eight
+    hundred and forty years, and had other sons and daughters. [5:14] Thus all the
+    days of Kenan were nine hundred and ten years; and he died. [5:15] When Mahalalel
+    had lived sixty-five years, he became the father of Jared. [5:16] Mahalalel lived
+    after the birth of Jared eight hundred thirty years, and had other sons and daughters.
+    [5:17] Thus all the days of Mahalalel were eight hundred ninety-five years; and
+    he died. [5:18] When Jared had lived one hundred sixty-two years he became the
+    father of Enoch. [5:19] Jared lived after the birth of Enoch eight hundred years,
+    and had other sons
+  - go with this man?" She said, "I will." [24:59] So they sent away their sister
+    Rebekah and her nurse along with Abraham's servant and his men. [24:60] And they
+    blessed Rebekah and said to her, "May you, our sister, become thousands of myriads;
+    may your offspring gain possession of the gates of their foes." [24:61] Then Rebekah
+    and her maids rose up, mounted the camels, and followed the man; thus the servant
+    took Rebekah, and went his way. [24:62] Now Isaac had come from Beer-lahai-roi,
+    and was settled in the Negeb. [24:63] Isaac went out in the evening to walk in
+    the field; and looking up, he saw camels coming. [24:64] And Rebekah looked up,
+    and when she saw Isaac, she slipped quickly from the camel, [24:65] and said to
+    the servant, "Who is
+- source_sentence: What did Abraham serve to the visitors while they ate under the
+    tree?
+  sentences:
+  - '[21:34] And Abraham resided as an alien many days in the land of the Philistines.  Chapter
+    22 [22:1] After these things God tested Abraham. He said to him, "Abraham!" And
+    he said, "Here I am." [22:2] He said, "Take your son, your only son Isaac, whom
+    you love, and go to the land of Moriah, and offer him there as a burnt offering
+    on one of the mountains that I shall show you." [22:3] So Abraham rose early in
+    the morning, saddled his donkey, and took two of his young men with him, and his
+    son Isaac; he cut the wood for the burnt offering, and set out and went to the
+    place in the distance that God had shown him. [22:4] On the third day Abraham
+    looked up and saw the place far away. [22:5] Then Abraham said to his young men,
+    "Stay here with the'
+  - tree. [18:5] Let me bring a little bread, that you may refresh yourselves, and
+    after that you may pass on - since you have come to your servant." So they said,
+    "Do as you have said." [18:6] And Abraham hastened into the tent to Sarah, and
+    said, "Make ready quickly three measures of choice flour, knead it, and make cakes.
+    " [18:7] Abraham ran to the herd, and took a calf, tender and good, and gave it
+    to the servant, who hastened to prepare it. [18:8] Then he took curds and milk
+    and the calf that he had prepared, and set it before them; and he stood by them
+    under the tree while they ate. [18:9] They said to him, "Where is your wife Sarah?"
+    And he said, "There, in the tent." [18:10] Then one said, "I will surely return
+    to you in due season,
+  - '[30:24] and she named him Joseph, saying, "May the LORD add to me another son!"
+    [30:25] When Rachel had borne Joseph, Jacob said to Laban, "Send me away, that
+    I may go to my own home and country. [30:26] Give me my wives and my children
+    for whom I have served you, and let me go; for you know very well the service
+    I have given you." [30:27] But Laban said to him, "If you will allow me to say
+    so, I have learned by divination that the LORD has blessed me because of you;
+    [30:28] name your wages, and I will give it." [30:29] Jacob said to him, "You
+    yourself know how I have served you, and how your cattle have fared with me. [30:30]
+    For you had little before I came, and it has increased abundantly; and the LORD
+    has blessed you wherever I turned.'
+pipeline_tag: sentence-similarity
+library_name: sentence-transformers
+metrics:
+- cosine_accuracy@1
+- cosine_accuracy@3
+- cosine_accuracy@5
+- cosine_accuracy@10
+- cosine_precision@1
+- cosine_precision@3
+- cosine_precision@5
+- cosine_precision@10
+- cosine_recall@1
+- cosine_recall@3
+- cosine_recall@5
+- cosine_recall@10
+- cosine_ndcg@10
+- cosine_mrr@10
+- cosine_map@100
+model-index:
+- name: SentenceTransformer based on Snowflake/snowflake-arctic-embed-l
+  results:
+  - task:
+      type: information-retrieval
+      name: Information Retrieval
+    dataset:
+      name: Unknown
+      type: unknown
+    metrics:
+    - type: cosine_accuracy@1
+      value: 0.75
+      name: Cosine Accuracy@1
+    - type: cosine_accuracy@3
+      value: 0.9375
+      name: Cosine Accuracy@3
+    - type: cosine_accuracy@5
+      value: 0.975
+      name: Cosine Accuracy@5
+    - type: cosine_accuracy@10
+      value: 0.9875
+      name: Cosine Accuracy@10
+    - type: cosine_precision@1
+      value: 0.75
+      name: Cosine Precision@1
+    - type: cosine_precision@3
+      value: 0.3125
+      name: Cosine Precision@3
+    - type: cosine_precision@5
+      value: 0.19499999999999998
+      name: Cosine Precision@5
+    - type: cosine_precision@10
+      value: 0.09874999999999998
+      name: Cosine Precision@10
+    - type: cosine_recall@1
+      value: 0.75
+      name: Cosine Recall@1
+    - type: cosine_recall@3
+      value: 0.9375
+      name: Cosine Recall@3
+    - type: cosine_recall@5
+      value: 0.975
+      name: Cosine Recall@5
+    - type: cosine_recall@10
+      value: 0.9875
+      name: Cosine Recall@10
+    - type: cosine_ndcg@10
+      value: 0.8820698787104944
+      name: Cosine Ndcg@10
+    - type: cosine_mrr@10
+      value: 0.8465773809523809
+      name: Cosine Mrr@10
+    - type: cosine_map@100
+      value: 0.8472718253968254
+      name: Cosine Map@100
+---
+
+# SentenceTransformer based on Snowflake/snowflake-arctic-embed-l
+
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [Snowflake/snowflake-arctic-embed-l](https://huggingface.co/Snowflake/snowflake-arctic-embed-l). It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
+
+## Model Details
+
+### Model Description
+- **Model Type:** Sentence Transformer
+- **Base model:** [Snowflake/snowflake-arctic-embed-l](https://huggingface.co/Snowflake/snowflake-arctic-embed-l) <!-- at revision d8fb21ca8d905d2832ee8b96c894d3298964346b -->
+- **Maximum Sequence Length:** 512 tokens
+- **Output Dimensionality:** 1024 dimensions
+- **Similarity Function:** Cosine Similarity
+<!-- - **Training Dataset:** Unknown -->
+<!-- - **Language:** Unknown -->
+<!-- - **License:** Unknown -->
+
+### Model Sources
+
+- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
+- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
+- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
+
+### Full Model Architecture
+
+```
+SentenceTransformer(
+  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
+  (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
+  (2): Normalize()
+)
+```
+
+## Usage
+
+### Direct Usage (Sentence Transformers)
+
+First install the Sentence Transformers library:
+
+```bash
+pip install -U sentence-transformers
+```
+
+Then you can load this model and run inference.
+```python
+from sentence_transformers import SentenceTransformer
+
+# Download from the 🤗 Hub
+model = SentenceTransformer("kcheng0816/finetuned_arctic_genesis")
+# Run inference
+sentences = [
+    'What did Abraham serve to the visitors while they ate under the tree?',
+    'tree. [18:5] Let me bring a little bread, that you may refresh yourselves, and after that you may pass on - since you have come to your servant." So they said, "Do as you have said." [18:6] And Abraham hastened into the tent to Sarah, and said, "Make ready quickly three measures of choice flour, knead it, and make cakes. " [18:7] Abraham ran to the herd, and took a calf, tender and good, and gave it to the servant, who hastened to prepare it. [18:8] Then he took curds and milk and the calf that he had prepared, and set it before them; and he stood by them under the tree while they ate. [18:9] They said to him, "Where is your wife Sarah?" And he said, "There, in the tent." [18:10] Then one said, "I will surely return to you in due season,',
+    '[21:34] And Abraham resided as an alien many days in the land of the Philistines.  Chapter 22 [22:1] After these things God tested Abraham. He said to him, "Abraham!" And he said, "Here I am." [22:2] He said, "Take your son, your only son Isaac, whom you love, and go to the land of Moriah, and offer him there as a burnt offering on one of the mountains that I shall show you." [22:3] So Abraham rose early in the morning, saddled his donkey, and took two of his young men with him, and his son Isaac; he cut the wood for the burnt offering, and set out and went to the place in the distance that God had shown him. [22:4] On the third day Abraham looked up and saw the place far away. [22:5] Then Abraham said to his young men, "Stay here with the',
+]
+embeddings = model.encode(sentences)
+print(embeddings.shape)
+# [3, 1024]
+
+# Get the similarity scores for the embeddings
+similarities = model.similarity(embeddings, embeddings)
+print(similarities.shape)
+# [3, 3]
+```
+
+<!--
+### Direct Usage (Transformers)
+
+<details><summary>Click to see the direct usage in Transformers</summary>
+
+</details>
+-->
+
+<!--
+### Downstream Usage (Sentence Transformers)
+
+You can finetune this model on your own dataset.
+
+<details><summary>Click to expand</summary>
+
+</details>
+-->
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+## Evaluation
+
+### Metrics
+
+#### Information Retrieval
+
+* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
+
+| Metric              | Value      |
+|:--------------------|:-----------|
+| cosine_accuracy@1   | 0.75       |
+| cosine_accuracy@3   | 0.9375     |
+| cosine_accuracy@5   | 0.975      |
+| cosine_accuracy@10  | 0.9875     |
+| cosine_precision@1  | 0.75       |
+| cosine_precision@3  | 0.3125     |
+| cosine_precision@5  | 0.195      |
+| cosine_precision@10 | 0.0987     |
+| cosine_recall@1     | 0.75       |
+| cosine_recall@3     | 0.9375     |
+| cosine_recall@5     | 0.975      |
+| cosine_recall@10    | 0.9875     |
+| **cosine_ndcg@10**  | **0.8821** |
+| cosine_mrr@10       | 0.8466     |
+| cosine_map@100      | 0.8473     |
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Dataset
+
+#### Unnamed Dataset
+
+* Size: 410 training samples
+* Columns: <code>sentence_0</code> and <code>sentence_1</code>
+* Approximate statistics based on the first 410 samples:
+  |         | sentence_0                                                                         | sentence_1                                                                          |
+  |:--------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|
+  | type    | string                                                                             | string                                                                              |
+  | details | <ul><li>min: 10 tokens</li><li>mean: 17.63 tokens</li><li>max: 31 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 206.17 tokens</li><li>max: 257 tokens</li></ul> |
+* Samples:
+  | sentence_0                                                                          | sentence_1                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |
+  |:------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+  | <code>What are the main themes explored in the Book of Genesis?</code>              | <code>The Book of Genesis</code>                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
+  | <code>How does the Book of Genesis describe the creation of the world?</code>       | <code>The Book of Genesis</code>                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
+  | <code>What did God create in the beginning according to the Book of Genesis?</code> | <code>THE BOOK OF GENESIS   1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50        Chapter 1  [1:1] In the beginning when God created the heavens and the earth, [1:2] the earth was a formless void and darkness covered the face of the deep, while a wind from God swept over the face of the waters. [1:3] Then God said, "Let there be light"; and there was light. [1:4] And God saw that the light was good; and God separated the light from the darkness. [1:5] God called the light Day, and the darkness he called Night. And there was evening and there was morning, the first day. [1:6] And God said, "Let there be</code> |
+* Loss: [<code>MatryoshkaLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#matryoshkaloss) with these parameters:
+  ```json
+  {
+      "loss": "MultipleNegativesRankingLoss",
+      "matryoshka_dims": [
+          768,
+          512,
+          256,
+          128,
+          64
+      ],
+      "matryoshka_weights": [
+          1,
+          1,
+          1,
+          1,
+          1
+      ],
+      "n_dims_per_step": -1
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `eval_strategy`: steps
+- `per_device_train_batch_size`: 10
+- `per_device_eval_batch_size`: 10
+- `num_train_epochs`: 10
+- `multi_dataset_batch_sampler`: round_robin
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `eval_strategy`: steps
+- `prediction_loss_only`: True
+- `per_device_train_batch_size`: 10
+- `per_device_eval_batch_size`: 10
+- `per_gpu_train_batch_size`: None
+- `per_gpu_eval_batch_size`: None
+- `gradient_accumulation_steps`: 1
+- `eval_accumulation_steps`: None
+- `torch_empty_cache_steps`: None
+- `learning_rate`: 5e-05
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `max_grad_norm`: 1
+- `num_train_epochs`: 10
+- `max_steps`: -1
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: {}
+- `warmup_ratio`: 0.0
+- `warmup_steps`: 0
+- `log_level`: passive
+- `log_level_replica`: warning
+- `log_on_each_node`: True
+- `logging_nan_inf_filter`: True
+- `save_safetensors`: True
+- `save_on_each_node`: False
+- `save_only_model`: False
+- `restore_callback_states_from_checkpoint`: False
+- `no_cuda`: False
+- `use_cpu`: False
+- `use_mps_device`: False
+- `seed`: 42
+- `data_seed`: None
+- `jit_mode_eval`: False
+- `use_ipex`: False
+- `bf16`: False
+- `fp16`: False
+- `fp16_opt_level`: O1
+- `half_precision_backend`: auto
+- `bf16_full_eval`: False
+- `fp16_full_eval`: False
+- `tf32`: None
+- `local_rank`: 0
+- `ddp_backend`: None
+- `tpu_num_cores`: None
+- `tpu_metrics_debug`: False
+- `debug`: []
+- `dataloader_drop_last`: False
+- `dataloader_num_workers`: 0
+- `dataloader_prefetch_factor`: None
+- `past_index`: -1
+- `disable_tqdm`: False
+- `remove_unused_columns`: True
+- `label_names`: None
+- `load_best_model_at_end`: False
+- `ignore_data_skip`: False
+- `fsdp`: []
+- `fsdp_min_num_params`: 0
+- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
+- `fsdp_transformer_layer_cls_to_wrap`: None
+- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
+- `deepspeed`: None
+- `label_smoothing_factor`: 0.0
+- `optim`: adamw_torch
+- `optim_args`: None
+- `adafactor`: False
+- `group_by_length`: False
+- `length_column_name`: length
+- `ddp_find_unused_parameters`: None
+- `ddp_bucket_cap_mb`: None
+- `ddp_broadcast_buffers`: False
+- `dataloader_pin_memory`: True
+- `dataloader_persistent_workers`: False
+- `skip_memory_metrics`: True
+- `use_legacy_prediction_loop`: False
+- `push_to_hub`: False
+- `resume_from_checkpoint`: None
+- `hub_model_id`: None
+- `hub_strategy`: every_save
+- `hub_private_repo`: None
+- `hub_always_push`: False
+- `gradient_checkpointing`: False
+- `gradient_checkpointing_kwargs`: None
+- `include_inputs_for_metrics`: False
+- `include_for_metrics`: []
+- `eval_do_concat_batches`: True
+- `fp16_backend`: auto
+- `push_to_hub_model_id`: None
+- `push_to_hub_organization`: None
+- `mp_parameters`: 
+- `auto_find_batch_size`: False
+- `full_determinism`: False
+- `torchdynamo`: None
+- `ray_scope`: last
+- `ddp_timeout`: 1800
+- `torch_compile`: False
+- `torch_compile_backend`: None
+- `torch_compile_mode`: None
+- `dispatch_batches`: None
+- `split_batches`: None
+- `include_tokens_per_second`: False
+- `include_num_input_tokens_seen`: False
+- `neftune_noise_alpha`: None
+- `optim_target_modules`: None
+- `batch_eval_metrics`: False
+- `eval_on_start`: False
+- `use_liger_kernel`: False
+- `eval_use_gather_object`: False
+- `average_tokens_across_devices`: False
+- `prompts`: None
+- `batch_sampler`: batch_sampler
+- `multi_dataset_batch_sampler`: round_robin
+
+</details>
+
+### Training Logs
+| Epoch  | Step | cosine_ndcg@10 |
+|:------:|:----:|:--------------:|
+| 1.0    | 41   | 0.8988         |
+| 1.2195 | 50   | 0.8824         |
+| 2.0    | 82   | 0.8775         |
+| 2.4390 | 100  | 0.8808         |
+| 3.0    | 123  | 0.8673         |
+| 3.6585 | 150  | 0.8634         |
+| 4.0    | 164  | 0.8735         |
+| 4.8780 | 200  | 0.8730         |
+| 5.0    | 205  | 0.8713         |
+| 6.0    | 246  | 0.8719         |
+| 6.0976 | 250  | 0.8765         |
+| 7.0    | 287  | 0.8848         |
+| 7.3171 | 300  | 0.8783         |
+| 8.0    | 328  | 0.8892         |
+| 8.5366 | 350  | 0.8881         |
+| 9.0    | 369  | 0.8821         |
+| 9.7561 | 400  | 0.8821         |
+| 10.0   | 410  | 0.8821         |
+
+
+### Framework Versions
+- Python: 3.11.11
+- Sentence Transformers: 3.4.1
+- Transformers: 4.49.0
+- PyTorch: 2.6.0
+- Accelerate: 1.3.0
+- Datasets: 3.3.2
+- Tokenizers: 0.21.0
+
+## Citation
+
+### BibTeX
+
+#### Sentence Transformers
+```bibtex
+@inproceedings{reimers-2019-sentence-bert,
+    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
+    author = "Reimers, Nils and Gurevych, Iryna",
+    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
+    month = "11",
+    year = "2019",
+    publisher = "Association for Computational Linguistics",
+    url = "https://arxiv.org/abs/1908.10084",
+}
+```
+
+#### MatryoshkaLoss
+```bibtex
+@misc{kusupati2024matryoshka,
+    title={Matryoshka Representation Learning},
+    author={Aditya Kusupati and Gantavya Bhatt and Aniket Rege and Matthew Wallingford and Aditya Sinha and Vivek Ramanujan and William Howard-Snyder and Kaifeng Chen and Sham Kakade and Prateek Jain and Ali Farhadi},
+    year={2024},
+    eprint={2205.13147},
+    archivePrefix={arXiv},
+    primaryClass={cs.LG}
+}
+```
+
+#### MultipleNegativesRankingLoss
+```bibtex
+@misc{henderson2017efficient,
+    title={Efficient Natural Language Response Suggestion for Smart Reply},
+    author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
+    year={2017},
+    eprint={1705.00652},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

config.json

@@ -0,0 +1,25 @@
+{
+  "_name_or_path": "Snowflake/snowflake-arctic-embed-l",
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.49.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

config_sentence_transformers.json

@@ -0,0 +1,12 @@
+{
+  "__version__": {
+    "sentence_transformers": "3.4.1",
+    "transformers": "4.49.0",
+    "pytorch": "2.6.0"
+  },
+  "prompts": {
+    "query": "Represent this sentence for searching relevant passages: "
+  },
+  "default_prompt_name": null,
+  "similarity_fn_name": "cosine"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d4941569208f7c8800d39c3274f39f4d2c4710f5d224ded0d44da0a2977d42d3
+size 1336413848

modules.json

@@ -0,0 +1,20 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  },
+  {
+    "idx": 2,
+    "name": "2",
+    "path": "2_Normalize",
+    "type": "sentence_transformers.models.Normalize"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 512,
+  "do_lower_case": false
+}

special_tokens_map.json

@@ -0,0 +1,37 @@
+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "[PAD]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,63 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "max_length": 512,
+  "model_max_length": 512,
+  "pad_to_multiple_of": null,
+  "pad_token": "[PAD]",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "[SEP]",
+  "stride": 0,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}