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my-model-MiniLM-Area

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lBober/my-model-MiniLM-Area

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  1. README.md +28 -13
  2. model.safetensors +1 -1
  3. runs/May25_20-57-55_54438e66731d/events.out.tfevents.1716670676.54438e66731d.31159.0 +3 -0
  4. runs/May25_21-02-04_54438e66731d/events.out.tfevents.1716670924.54438e66731d.32433.0 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -20,11 +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: 1.5091
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- - Accuracy: 0.4101
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- - F1: 0.3008
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- - Precision: 0.2560
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- - Recall: 0.4101
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  ## Model description
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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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- - num_epochs: 5
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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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- | 1.8054 | 1.0 | 81 | 1.7186 | 0.3741 | 0.2567 | 0.2028 | 0.3741 |
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- | 1.658 | 2.0 | 162 | 1.6347 | 0.3669 | 0.2477 | 0.1994 | 0.3669 |
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- | 1.5442 | 3.0 | 243 | 1.5759 | 0.3957 | 0.2674 | 0.2039 | 0.3957 |
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- | 1.465 | 4.0 | 324 | 1.5283 | 0.4388 | 0.3402 | 0.3001 | 0.4388 |
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- | 1.3915 | 5.0 | 405 | 1.5091 | 0.4101 | 0.3008 | 0.2560 | 0.4101 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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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: 1.4129
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+ - Accuracy: 0.5036
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+ - F1: 0.4909
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+ - Precision: 0.5021
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+ - Recall: 0.5036
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  ## Model description
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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: 30
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+ - eval_batch_size: 5
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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: 20
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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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+ | 1.8823 | 1.0 | 22 | 1.7754 | 0.3165 | 0.1522 | 0.1002 | 0.3165 |
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+ | 1.7966 | 2.0 | 44 | 1.6984 | 0.4029 | 0.2987 | 0.2682 | 0.4029 |
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+ | 1.7182 | 3.0 | 66 | 1.6278 | 0.4460 | 0.3334 | 0.2662 | 0.4460 |
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+ | 1.6204 | 4.0 | 88 | 1.6025 | 0.4388 | 0.3266 | 0.2619 | 0.4388 |
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+ | 1.5906 | 5.0 | 110 | 1.5386 | 0.4892 | 0.3664 | 0.3004 | 0.4892 |
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+ | 1.5192 | 6.0 | 132 | 1.5516 | 0.4317 | 0.3209 | 0.2596 | 0.4317 |
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+ | 1.4358 | 7.0 | 154 | 1.5271 | 0.4676 | 0.3495 | 0.2795 | 0.4676 |
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+ | 1.3818 | 8.0 | 176 | 1.4780 | 0.4748 | 0.3797 | 0.3403 | 0.4748 |
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+ | 1.314 | 9.0 | 198 | 1.4462 | 0.5180 | 0.4476 | 0.3974 | 0.5180 |
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+ | 1.2579 | 10.0 | 220 | 1.4591 | 0.5036 | 0.4265 | 0.3722 | 0.5036 |
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+ | 1.2336 | 11.0 | 242 | 1.4948 | 0.5108 | 0.4529 | 0.4399 | 0.5108 |
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+ | 1.1771 | 12.0 | 264 | 1.4809 | 0.5108 | 0.4500 | 0.4315 | 0.5108 |
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+ | 1.1311 | 13.0 | 286 | 1.4216 | 0.5540 | 0.5039 | 0.6025 | 0.5540 |
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+ | 1.0755 | 14.0 | 308 | 1.4449 | 0.5108 | 0.4819 | 0.5087 | 0.5108 |
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+ | 1.0362 | 15.0 | 330 | 1.4401 | 0.5324 | 0.5149 | 0.5126 | 0.5324 |
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+ | 1.0026 | 16.0 | 352 | 1.3924 | 0.5396 | 0.5192 | 0.5101 | 0.5396 |
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+ | 0.9734 | 17.0 | 374 | 1.4036 | 0.5180 | 0.5024 | 0.5116 | 0.5180 |
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+ | 0.949 | 18.0 | 396 | 1.3800 | 0.5252 | 0.5108 | 0.5189 | 0.5252 |
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+ | 0.9293 | 19.0 | 418 | 1.4091 | 0.5036 | 0.4895 | 0.4982 | 0.5036 |
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+ | 0.9185 | 20.0 | 440 | 1.4129 | 0.5036 | 0.4909 | 0.5021 | 0.5036 |
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  ### Framework versions
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