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End of training

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: Supabase/gte-small
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: v_best_model
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # v_best_model
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+
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+ This model is a fine-tuned version of [Supabase/gte-small](https://huggingface.co/Supabase/gte-small) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2700
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+ - Accuracy: 0.9437
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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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: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.639 | 1.0 | 21 | 1.3351 | 0.7606 |
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+ | 1.065 | 2.0 | 42 | 0.7793 | 0.8592 |
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+ | 0.6055 | 3.0 | 63 | 0.5200 | 0.8873 |
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+ | 0.3519 | 4.0 | 84 | 0.3832 | 0.9014 |
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+ | 0.2186 | 5.0 | 105 | 0.3277 | 0.9155 |
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+ | 0.1573 | 6.0 | 126 | 0.2844 | 0.9296 |
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+ | 0.118 | 7.0 | 147 | 0.3185 | 0.9014 |
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+ | 0.0948 | 8.0 | 168 | 0.2744 | 0.9437 |
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+ | 0.0831 | 9.0 | 189 | 0.2746 | 0.9437 |
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+ | 0.0778 | 10.0 | 210 | 0.2700 | 0.9437 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.2
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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