Instructions to use LexFerrinson/FirulaiModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LexFerrinson/FirulaiModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="LexFerrinson/FirulaiModel")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("LexFerrinson/FirulaiModel") model = AutoModelForTokenClassification.from_pretrained("LexFerrinson/FirulaiModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): e6dd533
Training in progress epoch 1
Browse files- README.md +4 -3
- tf_model.h5 +1 -1
README.md
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This model was trained from scratch on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 0.
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- Validation Loss: 0.
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- Train Precision: 0.0
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- Train Recall: 0.0
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- Train F1: 0.0
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- Train Accuracy: 0.9082
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- Epoch:
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## Model description
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| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
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|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
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| 0.2941 | 0.2539 | 0.0 | 0.0 | 0.0 | 0.9082 | 0 |
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### Framework versions
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This model was trained from scratch on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 0.2572
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- Validation Loss: 0.2342
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- Train Precision: 0.0
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- Train Recall: 0.0
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- Train F1: 0.0
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- Train Accuracy: 0.9082
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- Epoch: 1
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## Model description
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| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
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|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
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| 0.2941 | 0.2539 | 0.0 | 0.0 | 0.0 | 0.9082 | 0 |
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| 0.2572 | 0.2342 | 0.0 | 0.0 | 0.0 | 0.9082 | 1 |
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### Framework versions
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tf_model.h5
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version https://git-lfs.github.com/spec/v1
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size 265587984
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version https://git-lfs.github.com/spec/v1
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size 265587984
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