Text Classification
Transformers
TensorFlow
distilbert
generated_from_keras_callback
text-embeddings-inference
Instructions to use casarf/comment_model_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use casarf/comment_model_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="casarf/comment_model_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("casarf/comment_model_test") model = AutoModelForSequenceClassification.from_pretrained("casarf/comment_model_test") - Notebooks
- Google Colab
- Kaggle
Training in progress epoch 18
Browse files
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: 0.6270
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- Train Accuracy: 0.7349
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- Epoch:
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## Model description
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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: 0.2114
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- Validation Loss: 0.6270
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- Train Accuracy: 0.7349
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- Epoch: 18
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## Model description
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| 0.2037 | 0.6270 | 0.7349 | 15 |
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### Framework versions
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