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End of training

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  1. README.md +31 -31
  2. adapter_model.safetensors +1 -1
  3. runs/May28_06-56-21_2e90c5e16a11/events.out.tfevents.1716879382.2e90c5e16a11.393.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -17,12 +17,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [d0rj/rut5-base-summ](https://huggingface.co/d0rj/rut5-base-summ) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.9876
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- - Rouge1: 0.9333
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- - Rouge2: 0.8571
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- - Rougel: 0.9333
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- - Rougelsum: 0.9333
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- - Gen Len: 53.0
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  ## Model description
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@@ -54,31 +54,31 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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- | No log | 1.0 | 50 | 1.3299 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
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- | No log | 2.0 | 100 | 1.3140 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
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- | No log | 3.0 | 150 | 1.2892 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
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- | No log | 4.0 | 200 | 1.2606 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
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- | No log | 5.0 | 250 | 1.2296 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
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- | No log | 6.0 | 300 | 1.2008 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
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- | No log | 7.0 | 350 | 1.1741 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
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- | No log | 8.0 | 400 | 1.1422 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
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- | No log | 9.0 | 450 | 1.1200 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
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- | 2.0958 | 10.0 | 500 | 1.1019 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
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- | 2.0958 | 11.0 | 550 | 1.0857 | 0.0 | 0.0 | 0.0 | 0.0 | 10.0 |
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- | 2.0958 | 12.0 | 600 | 1.0655 | 0.0 | 0.0 | 0.0 | 0.0 | 10.0 |
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- | 2.0958 | 13.0 | 650 | 1.0515 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 53.0 |
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- | 2.0958 | 14.0 | 700 | 1.0397 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 53.0 |
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- | 2.0958 | 15.0 | 750 | 1.0287 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 53.0 |
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- | 2.0958 | 16.0 | 800 | 1.0212 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 53.0 |
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- | 2.0958 | 17.0 | 850 | 1.0138 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 53.0 |
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- | 2.0958 | 18.0 | 900 | 1.0068 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 53.0 |
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- | 2.0958 | 19.0 | 950 | 1.0022 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 53.0 |
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- | 1.879 | 20.0 | 1000 | 0.9969 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 53.0 |
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- | 1.879 | 21.0 | 1050 | 0.9937 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 53.0 |
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- | 1.879 | 22.0 | 1100 | 0.9915 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 53.0 |
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- | 1.879 | 23.0 | 1150 | 0.9893 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 53.0 |
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- | 1.879 | 24.0 | 1200 | 0.9875 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 53.0 |
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- | 1.879 | 25.0 | 1250 | 0.9876 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 53.0 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [d0rj/rut5-base-summ](https://huggingface.co/d0rj/rut5-base-summ) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9918
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+ - Rouge1: 0.9677
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+ - Rouge2: 0.8966
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+ - Rougel: 0.9677
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+ - Rougelsum: 0.9677
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+ - Gen Len: 79.0
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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+ | No log | 1.0 | 50 | 1.3458 | 0.0 | 0.0 | 0.0 | 0.0 | 20.0 |
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+ | No log | 2.0 | 100 | 1.3283 | 0.0 | 0.0 | 0.0 | 0.0 | 20.0 |
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+ | No log | 3.0 | 150 | 1.3000 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
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+ | No log | 4.0 | 200 | 1.2688 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
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+ | No log | 5.0 | 250 | 1.2354 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
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+ | No log | 6.0 | 300 | 1.2041 | 0.0 | 0.0 | 0.0 | 0.0 | 20.0 |
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+ | No log | 7.0 | 350 | 1.1791 | 0.0 | 0.0 | 0.0 | 0.0 | 10.0 |
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+ | No log | 8.0 | 400 | 1.1403 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
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+ | No log | 9.0 | 450 | 1.1153 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
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+ | 2.0999 | 10.0 | 500 | 1.0938 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
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+ | 2.0999 | 11.0 | 550 | 1.0813 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
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+ | 2.0999 | 12.0 | 600 | 1.0607 | 0.1176 | 0.0 | 0.1176 | 0.1176 | 35.0 |
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+ | 2.0999 | 13.0 | 650 | 1.0508 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 44.0 |
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+ | 2.0999 | 14.0 | 700 | 1.0386 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 44.0 |
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+ | 2.0999 | 15.0 | 750 | 1.0293 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 44.0 |
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+ | 2.0999 | 16.0 | 800 | 1.0210 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 44.0 |
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+ | 2.0999 | 17.0 | 850 | 1.0151 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 44.0 |
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+ | 2.0999 | 18.0 | 900 | 1.0084 | 0.0 | 0.0 | 0.0 | 0.0 | 10.0 |
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+ | 2.0999 | 19.0 | 950 | 1.0039 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 |
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+ | 1.8806 | 20.0 | 1000 | 0.9999 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 |
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+ | 1.8806 | 21.0 | 1050 | 0.9963 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 |
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+ | 1.8806 | 22.0 | 1100 | 0.9943 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 |
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+ | 1.8806 | 23.0 | 1150 | 0.9932 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 |
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+ | 1.8806 | 24.0 | 1200 | 0.9925 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 |
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+ | 1.8806 | 25.0 | 1250 | 0.9918 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 |
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  ### Framework versions
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