dannymartin commited on
Commit
6134b7e
1 Parent(s): 4b4ae69

Add SetFit model

Browse files
1_Pooling/config.json CHANGED
@@ -1,7 +1,7 @@
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README.md CHANGED
@@ -1,5 +1,5 @@
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  ---
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- base_model: avsolatorio/GIST-small-Embedding-v0
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  library_name: setfit
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  metrics:
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  - accuracy
@@ -164,11 +164,25 @@ widget:
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  '
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  inference: false
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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- # SetFit with avsolatorio/GIST-small-Embedding-v0
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- This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [avsolatorio/GIST-small-Embedding-v0](https://huggingface.co/avsolatorio/GIST-small-Embedding-v0) as the Sentence Transformer embedding model. A OneVsRestClassifier instance is used for classification.
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  The model has been trained using an efficient few-shot learning technique that involves:
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@@ -179,7 +193,7 @@ The model has been trained using an efficient few-shot learning technique that i
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  ### Model Description
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  - **Model Type:** SetFit
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- - **Sentence Transformer body:** [avsolatorio/GIST-small-Embedding-v0](https://huggingface.co/avsolatorio/GIST-small-Embedding-v0)
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  - **Classification head:** a OneVsRestClassifier instance
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  - **Maximum Sequence Length:** 512 tokens
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  - **Number of Classes:** 13 classes
@@ -193,6 +207,13 @@ The model has been trained using an efficient few-shot learning technique that i
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  - **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
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  - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
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  ## Uses
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  ### Direct Use for Inference
@@ -251,8 +272,8 @@ Add water and seasonings. Bring to a boil. Cover and simmer on low for 20 minu
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  | Word count | 4 | 4.2308 | 5 |
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  ### Training Hyperparameters
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- - batch_size: (32, 32)
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- - num_epochs: (1, 1)
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  - max_steps: -1
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  - sampling_strategy: oversampling
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  - body_learning_rate: (2e-05, 1e-05)
@@ -265,15 +286,14 @@ Add water and seasonings. Bring to a boil. Cover and simmer on low for 20 minu
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  - warmup_proportion: 0.1
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  - seed: 42
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  - eval_max_steps: -1
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- - load_best_model_at_end: True
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  ### Training Results
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- | Epoch | Step | Training Loss | Validation Loss |
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- |:-------:|:------:|:-------------:|:---------------:|
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- | 0.05 | 1 | 0.3162 | - |
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- | **1.0** | **20** | **-** | **0.2636** |
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- * The bold row denotes the saved checkpoint.
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  ### Framework Versions
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  - Python: 3.10.12
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  - SetFit: 1.0.3
 
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  ---
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+ base_model: sentence-transformers/paraphrase-mpnet-base-v2
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  library_name: setfit
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  metrics:
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  - accuracy
 
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  '
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  inference: false
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+ model-index:
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+ - name: SetFit with sentence-transformers/paraphrase-mpnet-base-v2
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+ results:
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+ - task:
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+ type: text-classification
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+ name: Text Classification
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+ dataset:
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+ name: Unknown
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+ type: unknown
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+ split: test
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+ metrics:
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+ - type: accuracy
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+ value: 0.0
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+ name: Accuracy
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  ---
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+ # SetFit with sentence-transformers/paraphrase-mpnet-base-v2
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+ This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2) as the Sentence Transformer embedding model. A OneVsRestClassifier instance is used for classification.
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  The model has been trained using an efficient few-shot learning technique that involves:
188
 
 
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  ### Model Description
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  - **Model Type:** SetFit
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+ - **Sentence Transformer body:** [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2)
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  - **Classification head:** a OneVsRestClassifier instance
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  - **Maximum Sequence Length:** 512 tokens
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  - **Number of Classes:** 13 classes
 
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  - **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
208
  - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
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+ ## Evaluation
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+
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+ ### Metrics
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+ | Label | Accuracy |
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+ |:--------|:---------|
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+ | **all** | 0.0 |
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+
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  ## Uses
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  ### Direct Use for Inference
 
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  | Word count | 4 | 4.2308 | 5 |
273
 
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  ### Training Hyperparameters
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+ - batch_size: (16, 2)
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+ - num_epochs: (1, 16)
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  - max_steps: -1
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  - sampling_strategy: oversampling
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  - body_learning_rate: (2e-05, 1e-05)
 
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  - warmup_proportion: 0.1
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  - seed: 42
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  - eval_max_steps: -1
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+ - load_best_model_at_end: False
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  ### Training Results
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+ | Epoch | Step | Training Loss | Validation Loss |
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+ |:------:|:----:|:-------------:|:---------------:|
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+ | 0.0256 | 1 | 0.1572 | - |
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+ | 1.0 | 39 | 0.0152 | 0.2304 |
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  ### Framework Versions
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  - Python: 3.10.12
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  - SetFit: 1.0.3
config.json CHANGED
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  }
 
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