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--- |
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pipeline_tag: sentence-similarity |
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tags: |
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- sentence-transformers |
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- feature-extraction |
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- sentence-similarity |
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--- |
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# DistilUSE Podcast Natural Questions |
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This is a [sentence-transformers](https://www.SBERT.net) model built for asymmetric semantic search of Podcast episodes. It replicates the fine-tuning process of Spotify's podcast search model, as [described here](https://www.pinecone.io/learn/spotify-podcast-search/). |
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## Usage (Sentence-Transformers) |
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Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed: |
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``` |
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pip install -U sentence-transformers |
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``` |
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Then you can use the model like this: |
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```python |
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from sentence_transformers import SentenceTransformer |
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sentences = ["podcast about climate change", "how to make money on the internet"] |
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model = SentenceTransformer('pinecone/distiluse-podcast-nq') |
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embeddings = model.encode(sentences) |
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``` |
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## Training |
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The model was trained with the parameters: |
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**DataLoader**: |
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`sentence_transformers.datasets.NoDuplicatesDataLoader.NoDuplicatesDataLoader` of length 3748 with parameters: |
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``` |
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{'batch_size': 64} |
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``` |
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**Loss**: |
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`sentence_transformers.losses.MultipleNegativesRankingLoss.MultipleNegativesRankingLoss` with parameters: |
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``` |
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{'scale': 20.0, 'similarity_fct': 'cos_sim'} |
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``` |
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Parameters of the fit()-Method: |
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``` |
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{ |
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"epochs": 1, |
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"evaluation_steps": 0, |
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"evaluator": "sentence_transformers.evaluation.RerankingEvaluator.RerankingEvaluator", |
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"max_grad_norm": 1, |
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"optimizer_class": "<class 'transformers.optimization.AdamW'>", |
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"optimizer_params": { |
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"lr": 2e-05 |
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}, |
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"scheduler": "WarmupLinear", |
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"steps_per_epoch": null, |
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"warmup_steps": 374, |
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"weight_decay": 0.01 |
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} |
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``` |
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## Full Model Architecture |
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``` |
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SentenceTransformer( |
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(0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: DistilBertModel |
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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}) |
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(2): Dense({'in_features': 768, 'out_features': 512, 'bias': True, 'activation_function': 'torch.nn.modules.activation.Tanh'}) |
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) |
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``` |
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## Citing & Authors |
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James Briggs, [How Spotify Uses Semantic Search for Podcasts](https://www.pinecone.io/learn/spotify-podcast-search/), Pinecone |
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