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End of training

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  1. README.md +20 -21
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,10 +18,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [avsolatorio/GIST-large-Embedding-v0](https://huggingface.co/avsolatorio/GIST-large-Embedding-v0) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2381
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- - F1: 0.5822
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- - Roc Auc: 0.7634
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- - Accuracy: 0.1786
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  ## Model description
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@@ -46,28 +46,27 @@ The following hyperparameters were used during training:
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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: 16
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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- | No log | 1.0 | 50 | 0.3147 | 0.0656 | 0.5250 | 0.0 |
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- | No log | 2.0 | 100 | 0.2808 | 0.2809 | 0.6082 | 0.0536 |
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- | No log | 3.0 | 150 | 0.2539 | 0.3854 | 0.6521 | 0.0357 |
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- | No log | 4.0 | 200 | 0.2451 | 0.4085 | 0.6582 | 0.0714 |
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- | No log | 5.0 | 250 | 0.2351 | 0.4365 | 0.6734 | 0.1071 |
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- | No log | 6.0 | 300 | 0.2361 | 0.4977 | 0.7133 | 0.125 |
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- | No log | 7.0 | 350 | 0.2325 | 0.5629 | 0.7433 | 0.1607 |
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- | No log | 8.0 | 400 | 0.2294 | 0.5488 | 0.7401 | 0.1964 |
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- | No log | 9.0 | 450 | 0.2336 | 0.5750 | 0.7567 | 0.1964 |
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- | 0.1718 | 10.0 | 500 | 0.2342 | 0.5695 | 0.7563 | 0.1964 |
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- | 0.1718 | 11.0 | 550 | 0.2354 | 0.5809 | 0.7648 | 0.1964 |
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- | 0.1718 | 12.0 | 600 | 0.2349 | 0.5862 | 0.7658 | 0.1786 |
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- | 0.1718 | 13.0 | 650 | 0.2390 | 0.5811 | 0.7645 | 0.1786 |
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- | 0.1718 | 14.0 | 700 | 0.2367 | 0.5841 | 0.7633 | 0.2143 |
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- | 0.1718 | 15.0 | 750 | 0.2376 | 0.5778 | 0.7606 | 0.1786 |
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- | 0.1718 | 16.0 | 800 | 0.2381 | 0.5822 | 0.7634 | 0.1786 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [avsolatorio/GIST-large-Embedding-v0](https://huggingface.co/avsolatorio/GIST-large-Embedding-v0) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2194
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+ - F1: 0.6392
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+ - Roc Auc: 0.7794
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+ - Accuracy: 0.1228
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  ## Model description
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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: 15
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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+ | No log | 1.0 | 50 | 0.3035 | 0.1236 | 0.5447 | 0.0 |
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+ | No log | 2.0 | 100 | 0.2696 | 0.3655 | 0.6420 | 0.0877 |
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+ | No log | 3.0 | 150 | 0.2468 | 0.3611 | 0.6390 | 0.0877 |
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+ | No log | 4.0 | 200 | 0.2387 | 0.4837 | 0.6999 | 0.0877 |
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+ | No log | 5.0 | 250 | 0.2311 | 0.5244 | 0.7164 | 0.0526 |
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+ | No log | 6.0 | 300 | 0.2215 | 0.5768 | 0.7326 | 0.1053 |
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+ | No log | 7.0 | 350 | 0.2242 | 0.6033 | 0.7593 | 0.0877 |
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+ | No log | 8.0 | 400 | 0.2155 | 0.6350 | 0.7624 | 0.0877 |
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+ | No log | 9.0 | 450 | 0.2227 | 0.6294 | 0.7746 | 0.1228 |
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+ | 0.1644 | 10.0 | 500 | 0.2156 | 0.6412 | 0.7772 | 0.1053 |
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+ | 0.1644 | 11.0 | 550 | 0.2176 | 0.6332 | 0.7715 | 0.1053 |
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+ | 0.1644 | 12.0 | 600 | 0.2182 | 0.6430 | 0.7816 | 0.1228 |
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+ | 0.1644 | 13.0 | 650 | 0.2190 | 0.6390 | 0.7794 | 0.1228 |
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+ | 0.1644 | 14.0 | 700 | 0.2184 | 0.6377 | 0.7788 | 0.1228 |
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+ | 0.1644 | 15.0 | 750 | 0.2194 | 0.6392 | 0.7794 | 0.1228 |
 
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  ### Framework versions
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