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GeneStory
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Classify-model-v1.2

Text Classification
Transformers
Safetensors
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Generated from Trainer
custom_code
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End of training

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  1. README.md +12 -11
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [thenlper/gte-small](https://huggingface.co/thenlper/gte-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5391
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- - Accuracy: 0.8661
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0002
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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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- | 1.6187 | 1.0 | 11 | 1.2743 | 0.6875 |
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- | 1.0031 | 2.0 | 22 | 0.8051 | 0.8482 |
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- | 0.5518 | 3.0 | 33 | 0.5952 | 0.8661 |
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- | 0.3103 | 4.0 | 44 | 0.5251 | 0.8571 |
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- | 0.2119 | 5.0 | 55 | 0.5139 | 0.8661 |
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- | 0.162 | 6.0 | 66 | 0.5225 | 0.8661 |
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- | 0.1419 | 7.0 | 77 | 0.5391 | 0.8661 |
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [thenlper/gte-small](https://huggingface.co/thenlper/gte-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5629
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+ - Accuracy: 0.9018
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 9.5e-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: 8
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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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+ | 1.7218 | 1.0 | 11 | 1.6062 | 0.5089 |
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+ | 1.4594 | 2.0 | 22 | 1.2322 | 0.7321 |
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+ | 1.1013 | 3.0 | 33 | 0.9340 | 0.8304 |
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+ | 0.8219 | 4.0 | 44 | 0.7659 | 0.875 |
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+ | 0.643 | 5.0 | 55 | 0.6768 | 0.8661 |
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+ | 0.5281 | 6.0 | 66 | 0.6099 | 0.8839 |
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+ | 0.4583 | 7.0 | 77 | 0.5751 | 0.8839 |
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+ | 0.4265 | 8.0 | 88 | 0.5629 | 0.9018 |
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  ### Framework versions
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