sentence-transformers safetensors bert sentence-similarity feature-extraction generated_from_trainer dataset_size:410 loss:MatryoshkaLoss loss:MultipleNegativesRankingLoss arxiv:1908.10084 arxiv:2205.13147 arxiv:1705.00652 base_model:Snowflake/snowflake-arctic-embed-l base_model:finetune:Snowflake/snowflake-arctic-embed-l model-index autotrain_compatible text-embeddings-inference endpoints_compatible region:us
---
base_model: Snowflake/snowflake-arctic-embed-l
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
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:410
- loss:MatryoshkaLoss
- loss:MultipleNegativesRankingLoss
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.'
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}
}
```

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