--- tags: - sentence-transformers - sentence-similarity - feature-extraction - generated_from_trainer - dataset_size:4200100 - loss:OrdinalProxyContrastiveLoss base_model: google/bert_uncased_L-2_H-128_A-2 widget: - source_sentence: Unless you have this jam-packed full of items, the unit collapses on itself. I never held it's shape therefore, making it hard to reach my items when I needed them. The silver metal pieces on the handle fell off soon after it arrived. I must have missed the "return by" date as I now am stuck with it. sentences: - very light weight. thin metal. nice looking just not a quality piece.it was okay for a kids gift. don't see it lasting very long as it will dent easy. - Fit fine - do not stay up. I haven’t washed or stretched, literally too out of bag and tried on for a bit of walking around the house and within 30 minutes they bunched down. Not sure the elastic will last either. Other than that, colors/patterns and general fabric is nice. - The Grinch seem to be of good quality. I would buy again. - source_sentence: I never got my item even though it said delivered. sentences: - Loved this hair brush! It's now much easier to detangle my frizzy hair after I wake up in the mornings. I wish I had found out about this much earlier. Thank you! - Good quality gasket and it was packaged well. Fit great as well. - Loved this hair brush! It's now much easier to detangle my frizzy hair after I wake up in the mornings. I wish I had found out about this much earlier. Thank you! - source_sentence: Was not a kit, was only a small individual box of lipstick. sentences: - Loved this hair brush! It's now much easier to detangle my frizzy hair after I wake up in the mornings. I wish I had found out about this much earlier. Thank you! - I don't know - for some reason I was disappointed in this product. It was as advertised but the pictures are so small and not put into a work out routine - seems scattered. Would have returned them but repackaging them would have been a pain. - These hooks work great for my boutique I have. I am able to hang scarves and different things from them including purses. They take up less space and last forever. The quality is excellent and so is the price! - source_sentence: Was not a kit, was only a small individual box of lipstick. sentences: - Had this Item for a year and it is already ripping everywhere and faded badly. I do not recommend. - Had this Item for a year and it is already ripping everywhere and faded badly. I do not recommend. - Judging from the title I thought there would be more of an espionage tilt to the story. I was wrong. This is about the Irish mob in Boston. And it’s a good read. Lots of action. Could use some more character development but that could be coming in future books. I like the main character Alex and would feel very comfortable with her watching my back. She’s a real kick-ass female. Will be reading more of the series definitely. Recommended. - source_sentence: Wrong size for my husband. I need to return them, unfortunately. sentences: - Battery life is pretty short. But it super fun while it lasts!! My nephews loved them! - These hooks work great for my boutique I have. I am able to hang scarves and different things from them including purses. They take up less space and last forever. The quality is excellent and so is the price! - I was so disappointed in this mascara. I really like Stila Products too, but it was just a clumpy mess on brush and hard to apply with the wand design. I had to be extra careful even just applying it because of how messy it was coming out of tube. Ended up returning it because Amazon is super great on their return policy on Prime items. pipeline_tag: sentence-similarity library_name: sentence-transformers --- # SentenceTransformer based on google/bert_uncased_L-2_H-128_A-2 This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2). It maps sentences & paragraphs to a 128-dimensional dense vector space and can be used for retrieval. ## Model Details ### Model Description - **Model Type:** Sentence Transformer - **Base model:** [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) - **Maximum Sequence Length:** 128 tokens - **Output Dimensionality:** 128 dimensions - **Similarity Function:** Cosine Similarity - **Supported Modality:** Text ### Model Sources - **Documentation:** [Sentence Transformers Documentation](https://sbert.net) - **Repository:** [Sentence Transformers on GitHub](https://github.com/huggingface/sentence-transformers) - **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers) ### Full Model Architecture ``` SentenceTransformer( (0): Transformer({'transformer_task': 'feature-extraction', 'modality_config': {'text': {'method': 'forward', 'method_output_name': 'last_hidden_state'}}, 'module_output_name': 'token_embeddings', 'architecture': 'BertModel'}) (1): Pooling({'embedding_dimension': 128, 'pooling_mode': 'mean', 'include_prompt': True}) ) ``` ## Usage ### Direct Usage (Sentence Transformers) First install the Sentence Transformers library: ```bash pip install -U sentence-transformers ``` Then you can load this model and run inference. ```python from sentence_transformers import SentenceTransformer # Download from the 🤗 Hub model = SentenceTransformer("swardiantara/bert-tiny-amazon_reviews-k5-adaptive-euclidean") # Run inference sentences = [ 'Wrong size for my husband. I need to return them, unfortunately.', 'Battery life is pretty short. But it super fun while it lasts!! My nephews loved them!', 'I was so disappointed in this mascara. I really like Stila Products too, but it was just a clumpy mess on brush and hard to apply with the wand design. I had to be extra careful even just applying it because of how messy it was coming out of tube. Ended up returning it because Amazon is super great on their return policy on Prime items.', ] embeddings = model.encode(sentences) print(embeddings.shape) # [3, 128] # Get the similarity scores for the embeddings similarities = model.similarity(embeddings, embeddings) print(similarities) # tensor([[1.0000, 0.9902, 0.9996], # [0.9902, 1.0000, 0.9896], # [0.9996, 0.9896, 1.0000]]) ``` Click to see the direct usage in Transformers --> Click to expand --> ## Training Details ### Training Dataset #### Unnamed Dataset * Size: 4,200,100 training samples * Columns: text_a , text_b , and label * Approximate statistics based on the first 100 samples: | | text_a | text_b | label | |:---------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------| | type | string | string | list | | modality | text | text | | | details | min: 15 tokens mean: 51.66 tokens max: 128 tokens | min: 17 tokens mean: 59.65 tokens max: 106 tokens | size: 2 elements | * Samples: | text_a | text_b | label | |:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------| | Arrived broken. Manufacturer defect. Two of the legs of the base were not completely formed, so there was no way to insert the casters. I unpackaged the entire chair and hardware before noticing this. So, I'll spend twice the amount of time boxing up the whole useless thing and send it back with a 1-star review of part of a chair I never got to sit in. I will go so far as to include a picture of what their injection molding and quality assurance process missed though. I will be hesitant to buy again. It makes me wonder if there aren't missing structures and supports that don't impede the assembly process. | I ordered this a while ago, even using prime it took over a month to get here, now that I finally got it, I only receved 6 of the 12! Im a little upset. It's still funny, but would not recomend for someone who needs foam quick and in bulk like i do. | [1.0, 0.0] | | Arrived broken. Manufacturer defect. Two of the legs of the base were not completely formed, so there was no way to insert the casters. I unpackaged the entire chair and hardware before noticing this. So, I'll spend twice the amount of time boxing up the whole useless thing and send it back with a 1-star review of part of a chair I never got to sit in. I will go so far as to include a picture of what their injection molding and quality assurance process missed though. I will be hesitant to buy again. It makes me wonder if there aren't missing structures and supports that don't impede the assembly process. | Had this Item for a year and it is already ripping everywhere and faded badly. I do not recommend. | [0.0, 0.25] | | Arrived broken. Manufacturer defect. Two of the legs of the base were not completely formed, so there was no way to insert the casters. I unpackaged the entire chair and hardware before noticing this. So, I'll spend twice the amount of time boxing up the whole useless thing and send it back with a 1-star review of part of a chair I never got to sit in. I will go so far as to include a picture of what their injection molding and quality assurance process missed though. I will be hesitant to buy again. It makes me wonder if there aren't missing structures and supports that don't impede the assembly process. | I was so disappointed in this mascara. I really like Stila Products too, but it was just a clumpy mess on brush and hard to apply with the wand design. I had to be extra careful even just applying it because of how messy it was coming out of tube. Ended up returning it because Amazon is super great on their return policy on Prime items. | [0.0, 0.25] | * Loss: __main__.OrdinalProxyContrastiveLoss ### Training Hyperparameters #### Non-Default Hyperparameters - `per_device_train_batch_size`: 1024 - `learning_rate`: 1e-05 - `load_best_model_at_end`: True #### All Hyperparameters Click to expand - `per_device_train_batch_size`: 1024 - `num_train_epochs`: 3 - `max_steps`: -1 - `learning_rate`: 1e-05 - `lr_scheduler_type`: linear - `lr_scheduler_kwargs`: None - `warmup_steps`: 0 - `optim`: adamw_torch - `optim_args`: None - `weight_decay`: 0.0 - `adam_beta1`: 0.9 - `adam_beta2`: 0.999 - `adam_epsilon`: 1e-08 - `optim_target_modules`: None - `gradient_accumulation_steps`: 1 - `average_tokens_across_devices`: True - `max_grad_norm`: 1.0 - `label_smoothing_factor`: 0.0 - `bf16`: False - `fp16`: False - `bf16_full_eval`: False - `fp16_full_eval`: False - `tf32`: None - `gradient_checkpointing`: False - `gradient_checkpointing_kwargs`: None - `torch_compile`: False - `torch_compile_backend`: None - `torch_compile_mode`: None - `use_liger_kernel`: False - `liger_kernel_config`: None - `use_cache`: False - `neftune_noise_alpha`: None - `torch_empty_cache_steps`: None - `auto_find_batch_size`: False - `log_on_each_node`: True - `logging_nan_inf_filter`: True -...
