Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use savioteless/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use savioteless/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="savioteless/test_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("savioteless/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("savioteless/test_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
061ca88
1
Parent(s): 2453007
google-play-sentiment-analysis
Browse files
README.md
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This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.
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- Accuracy: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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### Framework versions
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This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3686
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- Accuracy: 0.465
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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| No log | 1.0 | 125 | 1.4144 | 0.388 |
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| No log | 2.0 | 250 | 1.2860 | 0.481 |
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| No log | 3.0 | 375 | 1.3686 | 0.465 |
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### Framework versions
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model.safetensors
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runs/Dec06_01-54-51_3580dc5ae611/events.out.tfevents.1701827697.3580dc5ae611.15075.0
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training_args.bin
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