josejointriple
commited on
jointriple/brand_classification_2_20240705_model_3
Browse files- README.md +15 -27
- config.json +0 -0
- model.safetensors +1 -1
- training_args.bin +1 -1
README.md
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# results
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on
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It achieves the following results on the evaluation set:
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- Loss:
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- Accuracy: 0.
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- F1 Macro: 0.4565
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- Accuracy Balanced: 0.4775
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- F1 Micro: 0.8187
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- Precision Macro: 0.4745
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- Recall Macro: 0.4775
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- Precision Micro: 0.8187
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- Recall Micro: 0.8187
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 2048
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 8
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step
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| 4.8083 | 7.99 | 1184 | 4.5664 | 0.8187 | 0.4565 | 0.4775 | 0.8187 | 0.4745 | 0.4775 | 0.8187 | 0.8187 |
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### Framework versions
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# results
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.5162
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- Accuracy: 0.9213
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 128
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- eval_batch_size: 128
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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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 |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 6.0895 | 1.0 | 2371 | 5.7708 | 0.4478 |
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| 4.5154 | 2.0 | 4742 | 4.3046 | 0.7988 |
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| 3.5146 | 3.0 | 7113 | 3.1486 | 0.8932 |
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| 2.6148 | 4.0 | 9484 | 2.3505 | 0.9134 |
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| 2.1514 | 5.0 | 11855 | 1.8621 | 0.9178 |
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| 1.9055 | 6.0 | 14226 | 1.5997 | 0.9210 |
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| 1.635 | 7.0 | 16597 | 1.5162 | 0.9213 |
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### Framework versions
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config.json
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model.safetensors
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training_args.bin
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