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bert-base-uncased-FinedTuned

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End of training

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  1. README.md +20 -17
  2. events.out.tfevents.1719918241.1b83121686ed.1526.0 +2 -2
  3. model.safetensors +1 -1
README.md CHANGED
@@ -8,6 +8,8 @@ tags:
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  - generated_from_trainer
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  datasets:
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  - stsb_multi_mt
 
 
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  model-index:
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  - name: bert-base-uncased-FinedTuned
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  results: []
@@ -20,9 +22,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the stsb_multi_mt dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.7197
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- - Pearson: 0.2346
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- - Mse: 2.7197
 
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  ## Model description
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@@ -55,20 +58,20 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Pearson | Mse |
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- |:-------------:|:-------:|:-----:|:---------------:|:-------:|:------:|
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- | 0.051 | 5.5556 | 1000 | 2.8182 | 0.2432 | 2.8182 |
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- | 0.0623 | 11.1111 | 2000 | 2.8367 | 0.2164 | 2.8367 |
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- | 0.0471 | 16.6667 | 3000 | 2.7305 | 0.2126 | 2.7305 |
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- | 0.0357 | 22.2222 | 4000 | 2.6918 | 0.2324 | 2.6918 |
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- | 0.032 | 27.7778 | 5000 | 2.7902 | 0.2379 | 2.7902 |
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- | 0.0793 | 33.3333 | 6000 | 2.7368 | 0.2480 | 2.7368 |
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- | 0.0775 | 38.8889 | 7000 | 2.6499 | 0.2382 | 2.6499 |
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- | 0.0728 | 44.4444 | 8000 | 2.6974 | 0.2368 | 2.6974 |
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- | 0.0596 | 50.0 | 9000 | 2.7313 | 0.2302 | 2.7313 |
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- | 0.1012 | 55.5556 | 10000 | 2.7291 | 0.2332 | 2.7291 |
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- | 0.0644 | 61.1111 | 11000 | 2.7338 | 0.2315 | 2.7338 |
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- | 0.1595 | 66.6667 | 12000 | 2.7197 | 0.2346 | 2.7197 |
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  ### Framework versions
 
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  - generated_from_trainer
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  datasets:
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  - stsb_multi_mt
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+ metrics:
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+ - accuracy
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  model-index:
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  - name: bert-base-uncased-FinedTuned
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  results: []
 
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the stsb_multi_mt dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.6982
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+ - Pearson: 0.2449
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+ - Mse: 2.6982
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+ - Accuracy: 0.2574
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Pearson | Mse | Accuracy |
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+ |:-------------:|:-------:|:-----:|:---------------:|:-------:|:------:|:--------:|
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+ | 0.0221 | 5.5556 | 1000 | 2.7065 | 0.2549 | 2.7065 | 0.2553 |
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+ | 0.0511 | 11.1111 | 2000 | 2.7408 | 0.2264 | 2.7408 | 0.2509 |
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+ | 0.0223 | 16.6667 | 3000 | 2.7352 | 0.2356 | 2.7352 | 0.2473 |
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+ | 0.026 | 22.2222 | 4000 | 2.7210 | 0.2294 | 2.7210 | 0.2451 |
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+ | 0.011 | 27.7778 | 5000 | 2.6722 | 0.2438 | 2.6722 | 0.2545 |
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+ | 0.0222 | 33.3333 | 6000 | 2.6768 | 0.2369 | 2.6768 | 0.2538 |
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+ | 0.0466 | 38.8889 | 7000 | 2.6867 | 0.2414 | 2.6867 | 0.2589 |
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+ | 0.0355 | 44.4444 | 8000 | 2.7838 | 0.2298 | 2.7838 | 0.2538 |
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+ | 0.0349 | 50.0 | 9000 | 2.7550 | 0.2272 | 2.7550 | 0.2495 |
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+ | 0.0813 | 55.5556 | 10000 | 2.7215 | 0.2473 | 2.7215 | 0.2567 |
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+ | 0.0592 | 61.1111 | 11000 | 2.7262 | 0.2412 | 2.7262 | 0.2589 |
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+ | 0.1523 | 66.6667 | 12000 | 2.6982 | 0.2449 | 2.6982 | 0.2574 |
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  ### Framework versions
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