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atlasia
/
MorDernBERT-ep-1-lr-0.005

Sentence Similarity
sentence-transformers
Safetensors
modernbert
feature-extraction
Generated from Trainer
dataset_size:2818353
loss:CachedMultipleNegativesRankingLoss
Inference Endpoints
Model card Files Community
BounharAbdelaziz commited on
Commit
9920f26
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1 Parent(s): ec46e61

Add new SentenceTransformer model

Browse files
Files changed (10) hide show
  1. 1_Pooling/config.json +10 -0
  2. README.md +392 -0
  3. config.json +46 -0
  4. config_sentence_transformers.json +10 -0
  5. model.safetensors +3 -0
  6. modules.json +14 -0
  7. sentence_bert_config.json +4 -0
  8. special_tokens_map.json +37 -0
  9. tokenizer.json +0 -0
  10. tokenizer_config.json +945 -0
1_Pooling/config.json ADDED
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+ {
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+ "word_embedding_dimension": 768,
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+ "pooling_mode_cls_token": false,
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+ "pooling_mode_mean_tokens": true,
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+ "pooling_mode_max_tokens": false,
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+ "pooling_mode_mean_sqrt_len_tokens": false,
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+ "pooling_mode_weightedmean_tokens": false,
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+ "pooling_mode_lasttoken": false,
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+ "include_prompt": true
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+ }
README.md ADDED
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+ ---
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+ tags:
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+ - sentence-transformers
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+ - sentence-similarity
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+ - feature-extraction
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+ - generated_from_trainer
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+ - dataset_size:2818353
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+ - loss:CachedMultipleNegativesRankingLoss
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+ base_model: answerdotai/ModernBERT-base
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+ widget:
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+ - source_sentence: واش كا يحبس هاد الطوبيس في شارع ستونر؟
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+ sentences:
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+ - '{''ar'': ''هل هذه الحافلة تتوقف في شارع أستونر ؟''}'
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+ - tachicart/mo_darija_merged
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+ - tachicart/mo_darija_merged
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+ - source_sentence: العمال تما يقدرو يبدلو ليك الدولار بالفيتشات ديال الكازينو. مشينا؟
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+ sentences:
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+ - tachicart/mo_darija_merged
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+ - tachicart/mo_darija_merged
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+ - '{''ar'': ''يستطيع الصرافون أن يغيروا دولاراتك من أجل بقشيش الكازينو . هل نذهب
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+ ؟''}'
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+ - source_sentence: واخا توريني شي كبوط مضاد للماء؟
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+ sentences:
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+ - tachicart/mo_darija_merged
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+ - '{''ar'': ''هل لك أن ترنى معطفاً ضد الماء ؟''}'
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+ - tachicart/mo_darija_merged
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+ - source_sentence: فين كاين البلاطو رقم خمسة؟
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+ sentences:
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+ - tachicart/mo_darija_merged
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+ - tachicart/mo_darija_merged
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+ - '{''ar'': ''أين الرصيف رقم خمسة ؟''}'
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+ - source_sentence: شحال للمطار؟
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+ sentences:
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+ - tachicart/mo_darija_merged
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+ - tachicart/mo_darija_merged
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+ - '{''ar'': ''كم سأدفع للوصول إلى المطار ؟''}'
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+ datasets:
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+ - atlasia/AL-Atlas-Moroccan-Darija-Pretraining-Dataset
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+ pipeline_tag: sentence-similarity
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+ library_name: sentence-transformers
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+ ---
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+
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+ # SentenceTransformer based on answerdotai/ModernBERT-base
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+
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+ This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the [al-atlas-moroccan-darija-pretraining-dataset](https://huggingface.co/datasets/atlasia/AL-Atlas-Moroccan-Darija-Pretraining-Dataset) dataset. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
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+
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+ ## Model Details
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+
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+ ### Model Description
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+ - **Model Type:** Sentence Transformer
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+ - **Base model:** [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) <!-- at revision 5756c58a31a2478f9e62146021f48295a92c3da5 -->
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+ - **Maximum Sequence Length:** 8196 tokens
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+ - **Output Dimensionality:** 768 dimensions
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+ - **Similarity Function:** Cosine Similarity
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+ - **Training Dataset:**
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+ - [al-atlas-moroccan-darija-pretraining-dataset](https://huggingface.co/datasets/atlasia/AL-Atlas-Moroccan-Darija-Pretraining-Dataset)
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+ <!-- - **Language:** Unknown -->
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+ <!-- - **License:** Unknown -->
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+
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+ ### Model Sources
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+
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+ - **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
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+ - **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
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+ - **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
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+
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+ ### Full Model Architecture
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+
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+ ```
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+ SentenceTransformer(
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+ (0): Transformer({'max_seq_length': 8196, 'do_lower_case': False}) with Transformer model: ModernBertModel
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+ (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
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+ )
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+ ```
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+
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+ ## Usage
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+
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+ ### Direct Usage (Sentence Transformers)
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+
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+ First install the Sentence Transformers library:
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+
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+ ```bash
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+ pip install -U sentence-transformers
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+ ```
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+
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+ Then you can load this model and run inference.
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+ ```python
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+ from sentence_transformers import SentenceTransformer
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+
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+ # Download from the 🤗 Hub
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+ model = SentenceTransformer("BounharAbdelaziz/ModernBERT-base-0.005")
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+ # Run inference
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+ sentences = [
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+ 'شحال للمطار؟',
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+ 'tachicart/mo_darija_merged',
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+ "{'ar': 'كم سأدفع للوصول إلى المطار ؟'}",
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+ ]
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+ embeddings = model.encode(sentences)
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+ print(embeddings.shape)
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+ # [3, 768]
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+
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+ # Get the similarity scores for the embeddings
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+ similarities = model.similarity(embeddings, embeddings)
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+ print(similarities.shape)
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+ # [3, 3]
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+ ```
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+
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+ <!--
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+ ### Direct Usage (Transformers)
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+
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+ <details><summary>Click to see the direct usage in Transformers</summary>
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+
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+ </details>
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+ -->
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+
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+ <!--
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+ ### Downstream Usage (Sentence Transformers)
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+
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+ You can finetune this model on your own dataset.
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+
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+ <details><summary>Click to expand</summary>
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+
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+ </details>
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+ -->
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+
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+ <!--
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+ ### Out-of-Scope Use
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+
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+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
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+ -->
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+
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+ <!--
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+ ## Bias, Risks and Limitations
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+
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+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
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+ -->
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+
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+ <!--
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+ ### Recommendations
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+
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+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
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+ -->
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+
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+ ## Training Details
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+
145
+ ### Training Dataset
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+
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+ #### al-atlas-moroccan-darija-pretraining-dataset
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+
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+ * Dataset: [al-atlas-moroccan-darija-pretraining-dataset](https://huggingface.co/datasets/atlasia/AL-Atlas-Moroccan-Darija-Pretraining-Dataset) at [6668961](https://huggingface.co/datasets/atlasia/AL-Atlas-Moroccan-Darija-Pretraining-Dataset/tree/66689612b03f0d7a9528bf74ea30782dd2976569)
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+ * Size: 2,818,353 training samples
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+ * Columns: <code>text</code>, <code>dataset_source</code>, and <code>metadata</code>
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+ * Approximate statistics based on the first 1000 samples:
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+ | | text | dataset_source | metadata |
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+ |:--------|:-------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
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+ | type | string | string | string |
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+ | details | <ul><li>min: 3 tokens</li><li>mean: 334.62 tokens</li><li>max: 5020 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 13.0 tokens</li><li>max: 13 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 19.87 tokens</li><li>max: 26 tokens</li></ul> |
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+ * Samples:
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+ | text | dataset_source | metadata |
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+ |:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------|:------------------------------------------------------------------|
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+ | <code>سامي خضيرة : <br><br>الكابيتان فوقتنا كان هو كاسياس ولكن كنا كنحسو باللي راموس هو القائد الفعلي كان فيه الروح و الغرينتا ديال الاسبان .<br><br>ماتنساش كان معانا تا رونالدو كيهضر مع كولشي ويحفزنا ، و عادي تسمعو وسط الفيستير كيقول " خضيرة زير راسك وكون عدواني " ، " مسعود عطينا شوية من سحرك الكروي فالتيران " ونتا أدي ماريا حاول تشد الكرة وقصد المرمى " كان هادشي كيخلينا نعطيو كل ما فجهدنا <br><br>و بطبيعة الحال كان مورينيو الخطير فهاد الضومين ، و كانت المشكلة الكبيرة ديما هي كيفاش نوقفو ميسي ماشي غير حنا ولكن كاع الفراقي فداك الوقت .</code> | <code>atlasia/facebook_darija_dataset</code> | <code>{'pageName': "Football B'darija - فوتبول بالداريجة"}</code> |
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+ | <code>الأحداث كاتتطور بسرعة رهيبة ف بريتوريا !!<br><br>ميغيل كاردوزو المدرب السابق للترجي الرياضي التونسي وصل البارح بشكل مفاجئ لجنو�� افريقيا.. وصباح اليوم الصحافة المحلية كاتأكد انو ماميلودي سانداونز غاتقيل المدرب ديالها اليوم و غاتعين كاردوزو ك بديل !</code> | <code>atlasia/facebook_darija_dataset</code> | <code>{'pageName': "Football B'darija - فوتبول بالداريجة"}</code> |
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+ | <code>الريال و تحدي جديد هاد الليلة باش يرجعو للمنافسة ف التشامبيانزليغ قدام خصم أقل ما يتقال عليه انو عتيد هو اتلانتا بيرغامو وليدات العبقري جيانبييرو غاسبيريني..<br><br>الريال مؤخرا ورغم الشكوك اللي دايرة على الفريق والمشاكل الدفاعية و الإصابات اللي زادت ف الهشاشة ديال الدفاع ديالو الا انو رجع بقوة للمنافسة فالليغا واستغل الفترة د الفراغ اللي تا تعيشها البارسا حاليا باش يرجع على بعد نقطتين من الصدارة و عندو ماتش مؤجل مرشح بقوة يفوز فيه على فالنسيا ويطلع للقمة ..<br><br>الريال تانضن لا ربح اليوم غايمحي بشكل شبه كلي الغمامة اللي كاتطوف فوق منو من بدا الموسم و غايقوي ثقة الجمهور فيه و يرجع الثقة للمجموعة و غايرسم راسو ك رقم قوي ف المنافسة المفضلة ليه واحنا ديجا عارفين ان الريال diesel فرقة كاتديماري بشوية بشوية وفالفترات الحاسمة ف الموسم كاتورك على السانكيام فيتيس.</code> | <code>atlasia/facebook_darija_dataset</code> | <code>{'pageName': "Football B'darija - فوتبول بالداريجة"}</code> |
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+ * Loss: [<code>CachedMultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedmultiplenegativesrankingloss) with these parameters:
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+ ```json
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+ {
166
+ "scale": 20.0,
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+ "similarity_fct": "cos_sim"
168
+ }
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+ ```
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+
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+ ### Evaluation Dataset
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+
173
+ #### al-atlas-moroccan-darija-pretraining-dataset
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+
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+ * Dataset: [al-atlas-moroccan-darija-pretraining-dataset](https://huggingface.co/datasets/atlasia/AL-Atlas-Moroccan-Darija-Pretraining-Dataset) at [6668961](https://huggingface.co/datasets/atlasia/AL-Atlas-Moroccan-Darija-Pretraining-Dataset/tree/66689612b03f0d7a9528bf74ea30782dd2976569)
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+ * Size: 1,875 evaluation samples
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+ * Columns: <code>text</code>, <code>dataset_source</code>, and <code>metadata</code>
178
+ * Approximate statistics based on the first 1000 samples:
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+ | | text | dataset_source | metadata |
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+ |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|
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+ | type | string | string | string |
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+ | details | <ul><li>min: 5 tokens</li><li>mean: 27.22 tokens</li><li>max: 170 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 14.0 tokens</li><li>max: 14 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 33.41 tokens</li><li>max: 177 tokens</li></ul> |
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+ * Samples:
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+ | text | dataset_source | metadata |
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+ |:---------------------------------------------------------------------------------------------------------|:----------------------------------------|:-----------------------------------------------------------------------------------------------------------|
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+ | <code>كاين في اللاخر ديال هاد القاعة. انجيب ليك شويا دابا. و إلا حتاجيتي شي حاجا اخرى، قولها ليا.</code> | <code>tachicart/mo_darija_merged</code> | <code>{'ar': 'إنها في أخر القاعة . سوف آتي لك ببعض منها الآن . إذا أردت أي شيئاً آخر فقط أعلمني .'}</code> |
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+ | <code>واش كا دير التعديلات؟</code> | <code>tachicart/mo_darija_merged</code> | <code>{'ar': 'هل تقومون بعمل تعديلات ؟'}</code> |
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+ | <code>بغينا ناخدو طابلة حدا الشرجم.</code> | <code>tachicart/mo_darija_merged</code> | <code>{'ar': 'نريد مائدة بجانب النافذة .'}</code> |
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+ * Loss: [<code>CachedMultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedmultiplenegativesrankingloss) with these parameters:
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+ ```json
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+ {
192
+ "scale": 20.0,
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+ "similarity_fct": "cos_sim"
194
+ }
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+ ```
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+
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+ ### Training Hyperparameters
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+ #### Non-Default Hyperparameters
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+
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+ - `eval_strategy`: steps
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+ - `per_device_train_batch_size`: 128
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+ - `per_device_eval_batch_size`: 128
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+ - `learning_rate`: 0.005
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+ - `num_train_epochs`: 1
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+ - `warmup_ratio`: 0.05
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+ - `bf16`: True
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+
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+ #### All Hyperparameters
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+ <details><summary>Click to expand</summary>
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+
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+ - `overwrite_output_dir`: False
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+ - `do_predict`: False
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+ - `eval_strategy`: steps
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+ - `prediction_loss_only`: True
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+ - `per_device_train_batch_size`: 128
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+ - `per_device_eval_batch_size`: 128
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+ - `per_gpu_train_batch_size`: None
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+ - `per_gpu_eval_batch_size`: None
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+ - `gradient_accumulation_steps`: 1
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+ - `eval_accumulation_steps`: None
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+ - `torch_empty_cache_steps`: None
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+ - `learning_rate`: 0.005
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+ - `weight_decay`: 0.0
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+ - `adam_beta1`: 0.9
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+ - `adam_beta2`: 0.999
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+ - `adam_epsilon`: 1e-08
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+ - `max_grad_norm`: 1.0
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+ - `num_train_epochs`: 1
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+ - `max_steps`: -1
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+ - `lr_scheduler_type`: linear
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+ - `lr_scheduler_kwargs`: {}
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+ - `warmup_ratio`: 0.05
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+ - `warmup_steps`: 0
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+ - `log_level`: passive
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+ - `log_level_replica`: warning
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+ - `log_on_each_node`: True
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+ - `logging_nan_inf_filter`: True
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+ - `save_safetensors`: True
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+ - `save_on_each_node`: False
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+ - `save_only_model`: False
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+ - `restore_callback_states_from_checkpoint`: False
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+ - `no_cuda`: False
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+ - `use_cpu`: False
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+ - `use_mps_device`: False
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+ - `seed`: 42
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+ - `data_seed`: None
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+ - `jit_mode_eval`: False
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+ - `use_ipex`: False
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+ - `bf16`: True
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+ - `fp16`: False
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+ - `fp16_opt_level`: O1
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+ - `half_precision_backend`: auto
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+ - `bf16_full_eval`: False
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+ - `fp16_full_eval`: False
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+ - `tf32`: None
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+ - `local_rank`: 0
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+ - `ddp_backend`: None
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+ - `tpu_num_cores`: None
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+ - `tpu_metrics_debug`: False
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+ - `debug`: []
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+ - `dataloader_drop_last`: False
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+ - `dataloader_num_workers`: 0
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+ - `dataloader_prefetch_factor`: None
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+ - `past_index`: -1
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+ - `disable_tqdm`: False
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+ - `remove_unused_columns`: True
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+ - `label_names`: None
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+ - `load_best_model_at_end`: False
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+ - `ignore_data_skip`: False
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+ - `fsdp`: []
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+ - `fsdp_min_num_params`: 0
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+ - `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
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+ - `fsdp_transformer_layer_cls_to_wrap`: None
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+ - `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
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+ - `deepspeed`: None
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+ - `label_smoothing_factor`: 0.0
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+ - `optim`: adamw_torch
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+ - `optim_args`: None
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+ - `adafactor`: False
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+ - `group_by_length`: False
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+ - `length_column_name`: length
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+ - `ddp_find_unused_parameters`: None
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+ - `ddp_bucket_cap_mb`: None
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+ - `ddp_broadcast_buffers`: False
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+ - `dataloader_pin_memory`: True
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+ - `dataloader_persistent_workers`: False
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+ - `skip_memory_metrics`: True
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+ - `use_legacy_prediction_loop`: False
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+ - `push_to_hub`: False
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+ - `resume_from_checkpoint`: None
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+ - `hub_model_id`: None
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+ - `hub_strategy`: every_save
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+ - `hub_private_repo`: None
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+ - `hub_always_push`: False
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+ - `gradient_checkpointing`: False
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+ - `gradient_checkpointing_kwargs`: None
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+ - `include_inputs_for_metrics`: False
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+ - `include_for_metrics`: []
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+ - `eval_do_concat_batches`: True
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+ - `fp16_backend`: auto
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+ - `push_to_hub_model_id`: None
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+ - `push_to_hub_organization`: None
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+ - `mp_parameters`:
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+ - `auto_find_batch_size`: False
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+ - `full_determinism`: False
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+ - `torchdynamo`: None
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+ - `ray_scope`: last
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+ - `ddp_timeout`: 1800
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+ - `torch_compile`: False
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+ - `torch_compile_backend`: None
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+ - `torch_compile_mode`: None
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+ - `dispatch_batches`: None
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+ - `split_batches`: None
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+ - `include_tokens_per_second`: False
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+ - `include_num_input_tokens_seen`: False
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+ - `neftune_noise_alpha`: None
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+ - `optim_target_modules`: None
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+ - `batch_eval_metrics`: False
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+ - `eval_on_start`: False
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+ - `use_liger_kernel`: False
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+ - `eval_use_gather_object`: False
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+ - `average_tokens_across_devices`: False
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+ - `prompts`: None
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+ - `batch_sampler`: batch_sampler
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+ - `multi_dataset_batch_sampler`: proportional
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+
327
+ </details>
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+
329
+ ### Training Logs
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+ | Epoch | Step | Training Loss | Validation Loss |
331
+ |:------:|:-----:|:-------------:|:---------------:|
332
+ | 0.2271 | 5000 | 4.4677 | 4.8309 |
333
+ | 0.4542 | 10000 | 4.4206 | 4.8347 |
334
+ | 0.6812 | 15000 | 4.3974 | 4.8401 |
335
+ | 0.9083 | 20000 | 4.3905 | 4.8354 |
336
+
337
+
338
+ ### Framework Versions
339
+ - Python: 3.12.3
340
+ - Sentence Transformers: 3.3.1
341
+ - Transformers: 4.48.0.dev0
342
+ - PyTorch: 2.5.1+cu124
343
+ - Accelerate: 1.1.1
344
+ - Datasets: 3.1.0
345
+ - Tokenizers: 0.21.0
346
+
347
+ ## Citation
348
+
349
+ ### BibTeX
350
+
351
+ #### Sentence Transformers
352
+ ```bibtex
353
+ @inproceedings{reimers-2019-sentence-bert,
354
+ title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
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+ author = "Reimers, Nils and Gurevych, Iryna",
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+ booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
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+ month = "11",
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+ year = "2019",
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+ publisher = "Association for Computational Linguistics",
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+ url = "https://arxiv.org/abs/1908.10084",
361
+ }
362
+ ```
363
+
364
+ #### CachedMultipleNegativesRankingLoss
365
+ ```bibtex
366
+ @misc{gao2021scaling,
367
+ title={Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup},
368
+ author={Luyu Gao and Yunyi Zhang and Jiawei Han and Jamie Callan},
369
+ year={2021},
370
+ eprint={2101.06983},
371
+ archivePrefix={arXiv},
372
+ primaryClass={cs.LG}
373
+ }
374
+ ```
375
+
376
+ <!--
377
+ ## Glossary
378
+
379
+ *Clearly define terms in order to be accessible across audiences.*
380
+ -->
381
+
382
+ <!--
383
+ ## Model Card Authors
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+
385
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
386
+ -->
387
+
388
+ <!--
389
+ ## Model Card Contact
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+
391
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
392
+ -->
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