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YesaOuO
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ModernBERT-base-CTSP

Sentence Similarity
sentence-transformers
Safetensors
modernbert
feature-extraction
Generated from Trainer
dataset_size:1136292
loss:CachedMultipleNegativesRankingLoss
Eval Results
Model card Files Community
YesaOuO commited on
Commit
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1 Parent(s): 892a416

Add new SentenceTransformer model

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Files changed (10) hide show
  1. 1_Pooling/config.json +10 -0
  2. README.md +433 -0
  3. config.json +47 -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:1136292
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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: During the 1960s Willard Cochrane was U.S. Department of Agriculture's
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+ head agricultural economist under U.S. Secretary of Agriculture Orville Freeman.
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+ sentences:
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+ - Cosmic Smash publisher Sega, platform Dreamcast.
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+ - Willard Cochrane occupation Economist.
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+ - Willard Cochrane educated at Harvard University, educated at Montana State University,
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+ date of birth 15 May 1914.
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+ - source_sentence: Four Moons stars Antonio Velázquez, Alejandro de la Madrid, César
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+ Ramos, Gustavo Egelhaaf, Alonso Echánove, Alejandro Belmonte, Karina Gidi and
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+ Juan Manuel Bernal.
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+ sentences:
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+ - Four Moons cast member Juan Manuel Bernal, cast member Antonio Velázquez, cast
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+ member Alejandro de la Madrid, RTC film rating C.
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+ - Leukotriene C4 synthase ortholog Ltc4s, ortholog Ltc4s, instance of Gene.
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+ - Four Moons publication date 27 April 2015.
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+ - source_sentence: James B. Kirby (September 28, 1884 - June 9, 1971) was an American
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+ inventor and self-taught electrical engineer who focused Jim Kirby's career on
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+ "eliminating the drudgery of housework".
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+ sentences:
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+ - Jim Kirby sex or gender male.
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+ - Kimberlé Williams Crenshaw notable work Intersectionality, field of work Intersectionality.
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+ - Jim Kirby date of death 09 June 1971, occupation Inventor, date of birth 28 September
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+ 1884.
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+ - source_sentence: Isabel Montero de la Cámara began work in the Foreign Office on
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+ June 18, 1974. and was appointed ambassador on April 9, 1996.
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+ sentences:
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+ - Back in Baby 's Arms publication date 00 1969, instance of Album.
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+ - Isabel Montero de la Cámara occupation Diplomat, country of citizenship Costa
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+ Rica, date of birth 01 January 1942.
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+ - Isabel Montero de la Cámara position held Ambassador.
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+ - source_sentence: In 1842 Alvars married the harpist Melanie Lewy, a member of a
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+ Vienna-based family of musicians with whom Alvars frequently performed.
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+ sentences:
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+ - Elias Parish Alvars place of birth Teignmouth.
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+ - Olivia of Palermo date of death 10 June 0463, sex or gender female, feast day
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+ June 10.
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+ - Elias Parish Alvars spouse Melanie Lewy, place of death Vienna.
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+ datasets:
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+ - YesaOuO/TEKGEN-CTSP
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+ pipeline_tag: sentence-similarity
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+ library_name: sentence-transformers
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+ metrics:
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+ - cosine_accuracy
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+ model-index:
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+ - name: SentenceTransformer based on answerdotai/ModernBERT-base
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+ results:
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+ - task:
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+ type: triplet
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+ name: Triplet
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+ dataset:
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+ name: YesaOuO/TEKGEN CTSP
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+ type: YesaOuO/TEKGEN-CTSP
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+ metrics:
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+ - type: cosine_accuracy
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+ value: 0.916620671749115
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+ name: Cosine Accuracy
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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 [tekgen-ctsp](https://huggingface.co/datasets/YesaOuO/TEKGEN-CTSP) 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 8949b909ec900327062f0ebf497f51aef5e6f0c8 -->
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+ - **Maximum Sequence Length:** 8192 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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+ - [tekgen-ctsp](https://huggingface.co/datasets/YesaOuO/TEKGEN-CTSP)
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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': 8192, '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("YesaOuO/ModernBERT-base-CTSP")
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+ # Run inference
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+ sentences = [
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+ 'In 1842 Alvars married the harpist Melanie Lewy, a member of a Vienna-based family of musicians with whom Alvars frequently performed.',
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+ 'Elias Parish Alvars spouse Melanie Lewy, place of death Vienna.',
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+ 'Elias Parish Alvars place of birth Teignmouth.',
122
+ ]
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+ embeddings = model.encode(sentences)
124
+ print(embeddings.shape)
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+ # [3, 768]
126
+
127
+ # Get the similarity scores for the embeddings
128
+ similarities = model.similarity(embeddings, embeddings)
129
+ print(similarities.shape)
130
+ # [3, 3]
131
+ ```
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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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+
138
+ </details>
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+ -->
140
+
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+ <!--
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+ ### Downstream Usage (Sentence Transformers)
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+
144
+ You can finetune this model on your own dataset.
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+
146
+ <details><summary>Click to expand</summary>
147
+
148
+ </details>
149
+ -->
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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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+ -->
156
+
157
+ ## Evaluation
158
+
159
+ ### Metrics
160
+
161
+ #### Triplet
162
+
163
+ * Dataset: `YesaOuO/TEKGEN-CTSP`
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+ * Evaluated with [<code>TripletEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.TripletEvaluator)
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+
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+ | Metric | Value |
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+ |:--------------------|:-----------|
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+ | **cosine_accuracy** | **0.9166** |
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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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+
184
+ ### Training Dataset
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+
186
+ #### tekgen-ctsp
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+
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+ * Dataset: [tekgen-ctsp](https://huggingface.co/datasets/YesaOuO/TEKGEN-CTSP) at [8d091eb](https://huggingface.co/datasets/YesaOuO/TEKGEN-CTSP/tree/8d091ebc57b429b55add63e77a0408fa8dc3732b)
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+ * Size: 1,136,292 training samples
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+ * Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
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+ * Approximate statistics based on the first 1000 samples:
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+ | | anchor | positive | negative |
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+ |:--------|:------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|
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+ | type | string | string | string |
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+ | details | <ul><li>min: 11 tokens</li><li>mean: 38.01 tokens</li><li>max: 128 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 17.07 tokens</li><li>max: 47 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 17.02 tokens</li><li>max: 47 tokens</li></ul> |
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+ * Samples:
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+ | anchor | positive | negative |
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+ |:----------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------|
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+ | <code>1976 Swedish Grand Prix was the seventh round of the 1976 Formula One season and the ninth Swedish Grand Prix.</code> | <code>1976 Swedish Grand Prix point in time 13 June 1976, part of 1976 Formula One season.</code> | <code>1976 Swedish Grand Prix pole position Jody Scheckter, winner Jody Scheckter.</code> |
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+ | <code>1976 Swedish Grand Prix was the seventh round of the 1976 Formula One season and the ninth Swedish Grand Prix.</code> | <code>1976 Swedish Grand Prix point in time 13 June 1976, part of 1976 Formula One season.</code> | <code>1976 Swedish Grand Prix point in time 13 June 1976, country Sweden.</code> |
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+ | <code>1976 Swedish Grand Prix was the seventh round of the 1976 Formula One season and the ninth Swedish Grand Prix.</code> | <code>1976 Swedish Grand Prix point in time 13 June 1976, part of 1976 Formula One season.</code> | <code>1976 Swedish Grand Prix point in time 13 June 1976.</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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+ {
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+ "scale": 20.0,
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+ "similarity_fct": "cos_sim"
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+ }
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+ ```
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+
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+ ### Evaluation Dataset
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+
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+ #### tekgen-ctsp
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+
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+ * Dataset: [tekgen-ctsp](https://huggingface.co/datasets/YesaOuO/TEKGEN-CTSP) at [8d091eb](https://huggingface.co/datasets/YesaOuO/TEKGEN-CTSP/tree/8d091ebc57b429b55add63e77a0408fa8dc3732b)
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+ * Size: 10,866 evaluation samples
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+ * Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
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+ * Approximate statistics based on the first 1000 samples:
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+ | | anchor | positive | negative |
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+ |:--------|:------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|
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+ | type | string | string | string |
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+ | details | <ul><li>min: 13 tokens</li><li>mean: 40.18 tokens</li><li>max: 183 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 19.82 tokens</li><li>max: 62 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 19.82 tokens</li><li>max: 62 tokens</li></ul> |
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+ * Samples:
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+ | anchor | positive | negative |
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+ |:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------|
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+ | <code>Two men with prior criminal records, Dieter Degowski and Hans-Jürgen Rösner, went on the run for two days through Germany and the Netherlands.</code> | <code>Gladbeck hostage crisis country Netherlands, country Germany, participant Hans-Jürgen Rösner, participant Dieter Degowski.</code> | <code>Gladbeck hostage crisis end time 18 August 1988, point in time 18 August 1988, country Germany, start time 16 August 1988.</code> |
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+ | <code>The Gladbeck hostage crisis (known in Germany as the Gladbeck hostage drama) was a hostage-taking crisis that happened in August 1988 after an armed bank raid in Gladbeck, North Rhine-Westphalia, West Germany.</code> | <code>Gladbeck hostage crisis end time 18 August 1988, point in time 18 August 1988, country Germany, start time 16 August 1988.</code> | <code>Gladbeck hostage crisis country Netherlands, country Germany, participant Hans-Jürgen Rösner, participant Dieter Degowski.</code> |
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+ | <code>The album was originally released only on cassette tape before later being made available for digital download on iTunes and similar digital media stores.</code> | <code>Vongole Fisarmonica instance of Album.</code> | <code>Vongole Fisarmonica performer Those Darn Accordions, publication date 01 January 1992, instance of Album.</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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+ {
231
+ "scale": 20.0,
232
+ "similarity_fct": "cos_sim"
233
+ }
234
+ ```
235
+
236
+ ### Training Hyperparameters
237
+ #### Non-Default Hyperparameters
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+
239
+ - `per_device_train_batch_size`: 512
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+ - `per_device_eval_batch_size`: 512
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+ - `learning_rate`: 8e-05
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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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+ - `batch_sampler`: no_duplicates
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+
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+ #### All Hyperparameters
248
+ <details><summary>Click to expand</summary>
249
+
250
+ - `overwrite_output_dir`: False
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+ - `do_predict`: False
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+ - `eval_strategy`: no
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+ - `prediction_loss_only`: True
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+ - `per_device_train_batch_size`: 512
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+ - `per_device_eval_batch_size`: 512
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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`: 8e-05
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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
329
+ - `resume_from_checkpoint`: None
330
+ - `hub_model_id`: None
331
+ - `hub_strategy`: every_save
332
+ - `hub_private_repo`: None
333
+ - `hub_always_push`: False
334
+ - `gradient_checkpointing`: False
335
+ - `gradient_checkpointing_kwargs`: None
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+ - `include_inputs_for_metrics`: False
337
+ - `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
344
+ - `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
357
+ - `batch_eval_metrics`: False
358
+ - `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`: no_duplicates
364
+ - `multi_dataset_batch_sampler`: proportional
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+
366
+ </details>
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+
368
+ ### Training Logs
369
+ | Epoch | Step | Training Loss | YesaOuO/TEKGEN-CTSP_cosine_accuracy |
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+ |:------:|:----:|:-------------:|:-----------------------------------:|
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+ | -1 | -1 | - | 0.6585 |
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+ | 0.2252 | 500 | 0.6404 | - |
373
+ | 0.4505 | 1000 | 0.212 | - |
374
+ | 0.6757 | 1500 | 0.1764 | - |
375
+ | 0.9009 | 2000 | 0.1562 | - |
376
+ | -1 | -1 | - | 0.9166 |
377
+
378
+
379
+ ### Framework Versions
380
+ - Python: 3.11.11
381
+ - Sentence Transformers: 3.4.1
382
+ - Transformers: 4.49.0
383
+ - PyTorch: 2.6.0+cu124
384
+ - Accelerate: 1.5.2
385
+ - Datasets: 3.3.2
386
+ - Tokenizers: 0.21.1
387
+
388
+ ## Citation
389
+
390
+ ### BibTeX
391
+
392
+ #### Sentence Transformers
393
+ ```bibtex
394
+ @inproceedings{reimers-2019-sentence-bert,
395
+ title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
396
+ author = "Reimers, Nils and Gurevych, Iryna",
397
+ booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
398
+ month = "11",
399
+ year = "2019",
400
+ publisher = "Association for Computational Linguistics",
401
+ url = "https://arxiv.org/abs/1908.10084",
402
+ }
403
+ ```
404
+
405
+ #### CachedMultipleNegativesRankingLoss
406
+ ```bibtex
407
+ @misc{gao2021scaling,
408
+ title={Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup},
409
+ author={Luyu Gao and Yunyi Zhang and Jiawei Han and Jamie Callan},
410
+ year={2021},
411
+ eprint={2101.06983},
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