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all_abstracts_multi-qa-MiniLM-L6-cos-v1_final

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End of training

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  1. README.md +26 -26
  2. model.safetensors +1 -1
  3. runs/Apr29_00-45-43_PC-AJ/events.out.tfevents.1714344343.PC-AJ.39420.0 +2 -2
README.md CHANGED
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  ---
 
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  tags:
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  - generated_from_trainer
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- base_model: sentence-transformers/multi-qa-MiniLM-L6-cos-v1
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  metrics:
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  - accuracy
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  - precision
@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [sentence-transformers/multi-qa-MiniLM-L6-cos-v1](https://huggingface.co/sentence-transformers/multi-qa-MiniLM-L6-cos-v1) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.7795
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- - Accuracy: 0.4469
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- - Precision: 0.4469
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- - Recall: 0.4469
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- - F1: 0.4469
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  ## Model description
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@@ -42,9 +42,9 @@ More information needed
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  ### Training hyperparameters
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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: 4
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- - eval_batch_size: 4
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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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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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- |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 2.1337 | 1.0 | 687 | 1.9092 | 0.3508 | 0.3508 | 0.3508 | 0.3508 |
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- | 1.8555 | 2.0 | 1374 | 1.9211 | 0.4061 | 0.4061 | 0.4061 | 0.4061 |
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- | 1.5715 | 3.0 | 2061 | 1.8437 | 0.4556 | 0.4556 | 0.4556 | 0.4556 |
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- | 1.3431 | 4.0 | 2748 | 1.9205 | 0.4512 | 0.4512 | 0.4512 | 0.4512 |
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- | 1.1965 | 5.0 | 3435 | 2.3187 | 0.4425 | 0.4425 | 0.4425 | 0.4425 |
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- | 0.8733 | 6.0 | 4122 | 2.5876 | 0.4585 | 0.4585 | 0.4585 | 0.4585 |
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- | 0.742 | 7.0 | 4809 | 2.7835 | 0.4571 | 0.4571 | 0.4571 | 0.4571 |
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- | 0.6883 | 8.0 | 5496 | 2.9692 | 0.4687 | 0.4687 | 0.4687 | 0.4687 |
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- | 0.5149 | 9.0 | 6183 | 3.4857 | 0.4425 | 0.4425 | 0.4425 | 0.4425 |
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- | 0.4392 | 10.0 | 6870 | 3.3746 | 0.4425 | 0.4425 | 0.4425 | 0.4425 |
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- | 0.3495 | 11.0 | 7557 | 3.7080 | 0.4425 | 0.4425 | 0.4425 | 0.4425 |
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- | 0.2802 | 12.0 | 8244 | 3.5762 | 0.4469 | 0.4469 | 0.4469 | 0.4469 |
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- | 0.2958 | 13.0 | 8931 | 3.7652 | 0.4352 | 0.4352 | 0.4352 | 0.4352 |
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- | 0.2162 | 14.0 | 9618 | 3.7253 | 0.4410 | 0.4410 | 0.4410 | 0.4410 |
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- | 0.2158 | 15.0 | 10305 | 3.7795 | 0.4469 | 0.4469 | 0.4469 | 0.4469 |
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  ### Framework versions
 
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  ---
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+ base_model: sentence-transformers/multi-qa-MiniLM-L6-cos-v1
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  tags:
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  - generated_from_trainer
 
5
  metrics:
6
  - accuracy
7
  - precision
 
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  This model is a fine-tuned version of [sentence-transformers/multi-qa-MiniLM-L6-cos-v1](https://huggingface.co/sentence-transformers/multi-qa-MiniLM-L6-cos-v1) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.8218
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+ - Accuracy: 0.4629
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+ - Precision: 0.4629
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+ - Recall: 0.4629
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+ - F1: 0.4629
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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: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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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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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | No log | 1.0 | 172 | 2.2174 | 0.2926 | 0.2926 | 0.2926 | 0.2926 |
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+ | No log | 2.0 | 344 | 2.0265 | 0.3057 | 0.3057 | 0.3057 | 0.3057 |
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+ | 2.3643 | 3.0 | 516 | 1.9485 | 0.3712 | 0.3712 | 0.3712 | 0.3712 |
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+ | 2.3643 | 4.0 | 688 | 1.8710 | 0.4250 | 0.4250 | 0.4250 | 0.4250 |
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+ | 2.3643 | 5.0 | 860 | 1.8507 | 0.4338 | 0.4338 | 0.4338 | 0.4338 |
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+ | 1.8634 | 6.0 | 1032 | 1.8297 | 0.4469 | 0.4469 | 0.4469 | 0.4469 |
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+ | 1.8634 | 7.0 | 1204 | 1.7612 | 0.4658 | 0.4658 | 0.4658 | 0.4658 |
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+ | 1.8634 | 8.0 | 1376 | 1.8224 | 0.4600 | 0.4600 | 0.4600 | 0.4600 |
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+ | 1.5986 | 9.0 | 1548 | 1.7700 | 0.4629 | 0.4629 | 0.4629 | 0.4629 |
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+ | 1.5986 | 10.0 | 1720 | 1.7942 | 0.4672 | 0.4672 | 0.4672 | 0.4672 |
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+ | 1.5986 | 11.0 | 1892 | 1.8150 | 0.4643 | 0.4643 | 0.4643 | 0.4643 |
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+ | 1.3916 | 12.0 | 2064 | 1.8018 | 0.4585 | 0.4585 | 0.4585 | 0.4585 |
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+ | 1.3916 | 13.0 | 2236 | 1.8006 | 0.4745 | 0.4745 | 0.4745 | 0.4745 |
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+ | 1.3916 | 14.0 | 2408 | 1.8110 | 0.4614 | 0.4614 | 0.4614 | 0.4614 |
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+ | 1.274 | 15.0 | 2580 | 1.8218 | 0.4629 | 0.4629 | 0.4629 | 0.4629 |
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  ### Framework versions
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