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--- |
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license: apache-2.0 |
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base_model: sentence-transformers/paraphrase-MiniLM-L3-v2 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- napsternxg/nyt_ingredients |
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model-index: |
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- name: nyt_ingredients-crf-tagger-paraphrase-MiniLM-L3-v2 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# nyt_ingredients-crf-tagger-paraphrase-MiniLM-L3-v2 |
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This model is a fine-tuned version of [sentence-transformers/paraphrase-MiniLM-L3-v2](https://huggingface.co/sentence-transformers/paraphrase-MiniLM-L3-v2) on the nyt_ingredients dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 11.3870 |
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- Comment: {'precision': 0.018842530282637954, 'recall': 0.010174418604651164, 'f1': 0.01321378008494573, 'number': 1376} |
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- Name: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1758} |
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- Qty: {'precision': 0.1499119991717569, 'recall': 0.9986206896551724, 'f1': 0.26068953101089204, 'number': 1450} |
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- Range End: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 14} |
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- Unit: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1163} |
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- Overall Precision: 0.1405 |
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- Overall Recall: 0.2538 |
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- Overall F1: 0.1809 |
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- Overall Accuracy: 0.1528 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Comment | Name | Qty | Range End | Unit | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:----------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------:|:------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:| |
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| No log | 1.0 | 54 | 13.0360 | {'precision': 0.003246753246753247, 'recall': 0.0007267441860465116, 'f1': 0.001187648456057007, 'number': 1376} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1758} | {'precision': 0.142309205350118, 'recall': 0.9979310344827587, 'f1': 0.24909622998794975, 'number': 1450} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 14} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1163} | 0.1382 | 0.2513 | 0.1784 | 0.1432 | |
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| No log | 2.0 | 108 | 11.3870 | {'precision': 0.018842530282637954, 'recall': 0.010174418604651164, 'f1': 0.01321378008494573, 'number': 1376} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1758} | {'precision': 0.1499119991717569, 'recall': 0.9986206896551724, 'f1': 0.26068953101089204, 'number': 1450} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 14} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1163} | 0.1405 | 0.2538 | 0.1809 | 0.1528 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.0 |
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