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my-model-MiniLM-Area

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lBober/my-model-MiniLM-Area

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  1. README.md +23 -17
  2. model.safetensors +1 -1
  3. runs/May25_19-08-59_54438e66731d/events.out.tfevents.1716664140.54438e66731d.933.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -5,6 +5,9 @@ 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: my-model-MiniLM-Area
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  results: []
@@ -17,8 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [Microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/Microsoft/Multilingual-MiniLM-L12-H384) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.8344
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- - Accuracy: 0.1942
 
 
 
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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: 100
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- - eval_batch_size: 100
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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 |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.935 | 1.0 | 7 | 1.9251 | 0.2662 |
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- | 1.9185 | 2.0 | 14 | 1.9102 | 0.3022 |
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- | 1.8967 | 3.0 | 21 | 1.8908 | 0.1942 |
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- | 1.8698 | 4.0 | 28 | 1.8697 | 0.1942 |
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- | 1.8458 | 5.0 | 35 | 1.8549 | 0.1942 |
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- | 1.829 | 6.0 | 42 | 1.8467 | 0.1942 |
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- | 1.8184 | 7.0 | 49 | 1.8409 | 0.1942 |
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- | 1.8105 | 8.0 | 56 | 1.8371 | 0.1942 |
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- | 1.806 | 9.0 | 63 | 1.8351 | 0.1942 |
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- | 1.8108 | 10.0 | 70 | 1.8344 | 0.1942 |
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  ### Framework versions
 
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  - generated_from_trainer
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  metrics:
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  - accuracy
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+ - f1
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+ - precision
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+ - recall
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  model-index:
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  - name: my-model-MiniLM-Area
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  results: []
 
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  This model is a fine-tuned version of [Microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/Microsoft/Multilingual-MiniLM-L12-H384) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.3835
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+ - Accuracy: 0.4748
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+ - F1: 0.4280
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+ - Precision: 0.4147
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+ - Recall: 0.4748
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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: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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 | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 1.8171 | 1.0 | 81 | 1.7710 | 0.2302 | 0.0862 | 0.0530 | 0.2302 |
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+ | 1.7264 | 2.0 | 162 | 1.6322 | 0.4101 | 0.2695 | 0.2007 | 0.4101 |
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+ | 1.5603 | 3.0 | 243 | 1.5425 | 0.3885 | 0.2544 | 0.1943 | 0.3885 |
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+ | 1.4237 | 4.0 | 324 | 1.5997 | 0.4317 | 0.3424 | 0.2883 | 0.4317 |
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+ | 1.2819 | 5.0 | 405 | 1.5824 | 0.4101 | 0.3260 | 0.2763 | 0.4101 |
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+ | 1.1493 | 6.0 | 486 | 1.4762 | 0.4460 | 0.3670 | 0.4151 | 0.4460 |
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+ | 1.0688 | 7.0 | 567 | 1.4088 | 0.4748 | 0.4279 | 0.4418 | 0.4748 |
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+ | 0.9746 | 8.0 | 648 | 1.4380 | 0.4604 | 0.3957 | 0.3835 | 0.4604 |
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+ | 0.9039 | 9.0 | 729 | 1.4078 | 0.4748 | 0.4278 | 0.4147 | 0.4748 |
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+ | 0.8577 | 10.0 | 810 | 1.3835 | 0.4748 | 0.4280 | 0.4147 | 0.4748 |
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  ### Framework versions
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