Add new SentenceTransformer model.
Browse files- README.md +58 -31
- config.json +1 -1
- model.safetensors +1 -1
README.md
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- generated_from_trainer
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- dataset_size:208
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- loss:BatchSemiHardTripletLoss
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base_model: BAAI/bge-base-en
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widget:
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- source_sentence: '
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- euclidean_accuracy
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- max_accuracy
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model-index:
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- name: SentenceTransformer based on BAAI/bge-base-en
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results:
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- task:
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type: triplet
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type: bge-base-en-v1.5-train
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metrics:
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- type: cosine_accuracy
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value: 0.
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name: Cosine Accuracy
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- type: dot_accuracy
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value: 0.
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name: Dot Accuracy
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- type: manhattan_accuracy
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value: 0.
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name: Manhattan Accuracy
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- type: euclidean_accuracy
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value: 0.
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name: Euclidean Accuracy
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- type: max_accuracy
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value: 0.
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name: Max Accuracy
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- task:
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type: triplet
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type: bge-base-en-v1.5-eval
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metrics:
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- type: cosine_accuracy
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value: 0
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name: Cosine Accuracy
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- type: dot_accuracy
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value: 0.
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name: Dot Accuracy
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- type: manhattan_accuracy
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value: 0
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name: Manhattan Accuracy
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- type: euclidean_accuracy
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value: 0
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name: Euclidean Accuracy
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- type: max_accuracy
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value: 0
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name: Max Accuracy
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---
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# SentenceTransformer based on BAAI/bge-base-en
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This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [BAAI/bge-base-en](https://huggingface.co/BAAI/bge-base-en). 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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## Model Details
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### Model Description
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- **Model Type:** Sentence Transformer
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- **Base model:** [BAAI/bge-base-en](https://huggingface.co/BAAI/bge-base-en) <!-- at revision
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- **Maximum Sequence Length:** 512 tokens
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- **Output Dimensionality:** 768 tokens
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- **Similarity Function:** Cosine Similarity
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* Dataset: `bge-base-en-v1.5-train`
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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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| Metric | Value
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| cosine_accuracy | 0.
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| dot_accuracy | 0.
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| manhattan_accuracy | 0.
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| euclidean_accuracy | 0.
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| **max_accuracy** | **0.
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#### Triplet
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* Dataset: `bge-base-en-v1.5-eval`
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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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| Metric | Value
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-
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| cosine_accuracy | 0
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| dot_accuracy | 0.
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| manhattan_accuracy | 0
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| euclidean_accuracy | 0
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| **max_accuracy** | **0
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<!--
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## Bias, Risks and Limitations
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### Training Logs
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| Epoch | Step | bge-base-en-v1.5-eval_max_accuracy | bge-base-en-v1.5-train_max_accuracy |
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|:-----:|:----:|:----------------------------------:|:-----------------------------------:|
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| 0 | 0 | - | 0.
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| 5.0 | 65 | 0
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### Framework Versions
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- generated_from_trainer
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- dataset_size:208
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- loss:BatchSemiHardTripletLoss
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base_model: BAAI/bge-base-en-v1.5
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widget:
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- source_sentence: '
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- euclidean_accuracy
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- max_accuracy
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model-index:
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+
- name: SentenceTransformer based on BAAI/bge-base-en-v1.5
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results:
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- task:
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type: triplet
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type: bge-base-en-v1.5-train
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metrics:
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- type: cosine_accuracy
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value: 0.8461538461538461
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name: Cosine Accuracy
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- type: dot_accuracy
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value: 0.15384615384615385
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name: Dot Accuracy
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- type: manhattan_accuracy
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value: 0.8509615384615384
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name: Manhattan Accuracy
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- type: euclidean_accuracy
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value: 0.8461538461538461
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name: Euclidean Accuracy
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- type: max_accuracy
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value: 0.8509615384615384
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name: Max Accuracy
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- task:
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type: triplet
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type: bge-base-en-v1.5-eval
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metrics:
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- type: cosine_accuracy
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value: 1.0
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name: Cosine Accuracy
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- type: dot_accuracy
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value: 0.0
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name: Dot Accuracy
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- type: manhattan_accuracy
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value: 1.0
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name: Manhattan Accuracy
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- type: euclidean_accuracy
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value: 1.0
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name: Euclidean Accuracy
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- type: max_accuracy
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value: 1.0
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name: Max Accuracy
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- type: cosine_accuracy
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value: 1.0
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name: Cosine Accuracy
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- type: dot_accuracy
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value: 0.0
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name: Dot Accuracy
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- type: manhattan_accuracy
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value: 1.0
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name: Manhattan Accuracy
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- type: euclidean_accuracy
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value: 1.0
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name: Euclidean Accuracy
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- type: max_accuracy
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value: 1.0
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name: Max Accuracy
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---
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# SentenceTransformer based on BAAI/bge-base-en-v1.5
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+
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5). 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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## Model Details
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### Model Description
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- **Model Type:** Sentence Transformer
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- **Base model:** [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) <!-- at revision a5beb1e3e68b9ab74eb54cfd186867f64f240e1a -->
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- **Maximum Sequence Length:** 512 tokens
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- **Output Dimensionality:** 768 tokens
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- **Similarity Function:** Cosine Similarity
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* Dataset: `bge-base-en-v1.5-train`
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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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| Metric | Value |
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|:-------------------|:----------|
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| cosine_accuracy | 0.8462 |
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| dot_accuracy | 0.1538 |
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| manhattan_accuracy | 0.851 |
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| euclidean_accuracy | 0.8462 |
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| **max_accuracy** | **0.851** |
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#### Triplet
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* Dataset: `bge-base-en-v1.5-eval`
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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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| Metric | Value |
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|:-------------------|:--------|
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| cosine_accuracy | 1.0 |
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| dot_accuracy | 0.0 |
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| manhattan_accuracy | 1.0 |
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| euclidean_accuracy | 1.0 |
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| **max_accuracy** | **1.0** |
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#### Triplet
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* Dataset: `bge-base-en-v1.5-eval`
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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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| Metric | Value |
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|:-------------------|:--------|
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| cosine_accuracy | 1.0 |
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| dot_accuracy | 0.0 |
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| manhattan_accuracy | 1.0 |
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| euclidean_accuracy | 1.0 |
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| **max_accuracy** | **1.0** |
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<!--
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## Bias, Risks and Limitations
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### Training Logs
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| Epoch | Step | bge-base-en-v1.5-eval_max_accuracy | bge-base-en-v1.5-train_max_accuracy |
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|:-----:|:----:|:----------------------------------:|:-----------------------------------:|
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| 0 | 0 | - | 0.8510 |
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| 5.0 | 65 | 1.0 | - |
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### Framework Versions
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config.json
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{
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"_name_or_path": "BAAI/bge-base-en",
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"architectures": [
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"BertModel"
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],
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{
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"_name_or_path": "BAAI/bge-base-en-v1.5",
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"architectures": [
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"BertModel"
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],
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 437951328
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version https://git-lfs.github.com/spec/v1
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size 437951328
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