Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use cloudwoowoo/zooguide_bert_checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cloudwoowoo/zooguide_bert_checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cloudwoowoo/zooguide_bert_checkpoints")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cloudwoowoo/zooguide_bert_checkpoints") model = AutoModelForSequenceClassification.from_pretrained("cloudwoowoo/zooguide_bert_checkpoints") - Notebooks
- Google Colab
- Kaggle
cloudwoowoo/zooguide-bert-animal-fact-assistant
Browse files- README.md +19 -0
- model.safetensors +1 -1
README.md
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base_model: distilbert-base-uncased
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tags:
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- generated_from_trainer
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model-index:
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- name: zooguide_bert_checkpoints
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results: []
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# zooguide_bert_checkpoints
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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## Model description
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- lr_scheduler_type: linear
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- num_epochs: 7
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### Framework versions
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- Transformers 5.0.0
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base_model: distilbert-base-uncased
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: zooguide_bert_checkpoints
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results: []
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# zooguide_bert_checkpoints
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0865
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- Accuracy: 0.9667
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- Macro F1: 0.9663
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## Model description
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- lr_scheduler_type: linear
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- num_epochs: 7
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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| 1.2682 | 1.0 | 132 | 0.2280 | 0.9689 | 0.9691 |
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| 0.1257 | 2.0 | 264 | 0.1087 | 0.9689 | 0.9692 |
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| 0.0717 | 3.0 | 396 | 0.0695 | 0.98 | 0.9798 |
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| 0.0612 | 4.0 | 528 | 0.0621 | 0.9711 | 0.9711 |
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| 0.0493 | 5.0 | 660 | 0.0580 | 0.9689 | 0.9691 |
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| 0.0436 | 6.0 | 792 | 0.0607 | 0.9667 | 0.9669 |
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| 0.0403 | 7.0 | 924 | 0.0628 | 0.96 | 0.9603 |
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### Framework versions
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- Transformers 5.0.0
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model.safetensors
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