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): a81296c
Training in progress epoch 3
Browse files- README.md +4 -3
- tf_model.h5 +1 -1
README.md
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) 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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| 0.9805 | 0.8370 | 0.2727 | 0.1034 | 0.15 | 0.8924 | 0 |
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| 0.8416 | 0.7234 | 0.0 | 0.0 | 0.0 | 0.9051 | 1 |
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| 0.7323 | 0.6383 | 0.0 | 0.0 | 0.0 | 0.9082 | 2 |
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### Framework versions
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 0.6500
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- Validation Loss: 0.5786
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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: 3
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## Model description
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| 0.9805 | 0.8370 | 0.2727 | 0.1034 | 0.15 | 0.8924 | 0 |
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| 0.8416 | 0.7234 | 0.0 | 0.0 | 0.0 | 0.9051 | 1 |
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| 0.7323 | 0.6383 | 0.0 | 0.0 | 0.0 | 0.9082 | 2 |
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| 0.6500 | 0.5786 | 0.0 | 0.0 | 0.0 | 0.9082 | 3 |
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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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oid sha256:cad3523e56a303270bb916e99b68b29cd3c7baf29d766ee7089f82d8cbe28613
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size 265587984
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