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mt5-large-finetuned-scope-summarization

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  1. README.md +25 -25
  2. model.safetensors +1 -1
  3. runs/Feb25_17-56-51_nbqbdwuqbg/events.out.tfevents.1708883820.nbqbdwuqbg.1626.0 +3 -0
  4. runs/Feb25_17-56-51_nbqbdwuqbg/events.out.tfevents.1708884192.nbqbdwuqbg.1626.1 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -17,11 +17,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 7.7968
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- - Rouge1: 8.9288
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- - Rouge2: 2.5195
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- - Rougel: 8.1326
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- - Rougelsum: 8.2266
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  ## Model description
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@@ -52,26 +52,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
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- | 24.9681 | 1.0 | 13 | 14.1263 | 9.679 | 1.2781 | 9.2044 | 9.2028 |
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- | 19.4912 | 2.0 | 26 | 13.8332 | 10.3322 | 2.2934 | 10.0898 | 9.9917 |
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- | 18.9675 | 3.0 | 39 | 14.5743 | 10.644 | 2.4553 | 10.4176 | 10.3855 |
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- | 23.2647 | 4.0 | 52 | 16.1424 | 9.4387 | 1.9352 | 8.8508 | 8.8573 |
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- | 25.5379 | 5.0 | 65 | 16.1511 | 8.9967 | 2.3549 | 8.6046 | 8.666 |
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- | 23.0787 | 6.0 | 78 | 15.0432 | 9.4838 | 2.3778 | 9.0507 | 9.1552 |
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- | 20.5359 | 7.0 | 91 | 12.4876 | 8.9692 | 2.5655 | 8.5533 | 8.6442 |
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- | 18.6638 | 8.0 | 104 | 10.5506 | 10.5377 | 2.5387 | 9.4585 | 9.3817 |
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- | 15.6668 | 9.0 | 117 | 10.4213 | 11.1515 | 2.3781 | 10.5545 | 10.6241 |
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- | 16.0823 | 10.0 | 130 | 9.7474 | 11.3564 | 2.6133 | 10.5169 | 10.5736 |
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- | 16.189 | 11.0 | 143 | 9.3992 | 10.5378 | 3.3175 | 9.2739 | 9.4737 |
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- | 14.6943 | 12.0 | 156 | 9.1679 | 9.8364 | 2.942 | 8.991 | 9.0988 |
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- | 13.9725 | 13.0 | 169 | 9.4899 | 9.1523 | 2.6655 | 8.499 | 8.6962 |
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- | 14.0998 | 14.0 | 182 | 8.4480 | 9.7567 | 2.9029 | 8.2077 | 8.3139 |
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- | 13.2 | 15.0 | 195 | 8.2385 | 9.9148 | 2.9029 | 8.1975 | 8.3074 |
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- | 13.1084 | 16.0 | 208 | 8.0442 | 8.1004 | 2.2435 | 7.4792 | 7.5977 |
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- | 13.6186 | 17.0 | 221 | 7.9349 | 8.2995 | 2.2435 | 7.4792 | 7.5977 |
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- | 12.6013 | 18.0 | 234 | 7.8921 | 8.5692 | 2.5238 | 7.7018 | 7.8229 |
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- | 12.8011 | 19.0 | 247 | 7.8561 | 8.5692 | 2.5238 | 7.7018 | 7.8229 |
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- | 12.9507 | 20.0 | 260 | 7.7968 | 8.9288 | 2.5195 | 8.1326 | 8.2266 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 8.2775
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+ - Rouge1: 5.918
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+ - Rouge2: 1.0667
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+ - Rougel: 5.7247
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+ - Rougelsum: 5.552
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
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+ | 27.8719 | 1.0 | 13 | 15.8303 | 9.9779 | 0.8912 | 8.8304 | 8.8653 |
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+ | 25.4142 | 2.0 | 26 | 20.3410 | 11.3301 | 1.0662 | 9.8807 | 9.8442 |
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+ | 24.8026 | 3.0 | 39 | 16.5876 | 11.1912 | 1.5008 | 9.9776 | 9.9685 |
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+ | 23.7918 | 4.0 | 52 | 14.0667 | 11.5953 | 1.6391 | 10.2961 | 10.1512 |
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+ | 21.945 | 5.0 | 65 | 12.3075 | 10.6522 | 1.2121 | 10.0748 | 10.0261 |
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+ | 18.8588 | 6.0 | 78 | 11.8270 | 11.4944 | 1.4152 | 9.9891 | 9.9505 |
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+ | 16.587 | 7.0 | 91 | 10.7425 | 9.9989 | 1.425 | 8.9661 | 8.9811 |
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+ | 15.9949 | 8.0 | 104 | 10.2228 | 10.0086 | 1.6533 | 8.9911 | 9.0047 |
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+ | 15.2301 | 9.0 | 117 | 11.2979 | 9.2011 | 1.425 | 8.9267 | 8.8763 |
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+ | 14.9655 | 10.0 | 130 | 11.3654 | 9.3934 | 1.6533 | 8.9243 | 8.8443 |
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+ | 14.7982 | 11.0 | 143 | 10.7718 | 8.5085 | 1.4133 | 8.0936 | 8.0127 |
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+ | 13.5222 | 12.0 | 156 | 10.0961 | 7.849 | 1.1637 | 7.3283 | 7.1943 |
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+ | 13.0959 | 13.0 | 169 | 9.4677 | 8.0846 | 1.1637 | 7.1215 | 7.0501 |
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+ | 13.0554 | 14.0 | 182 | 8.9576 | 7.0454 | 1.2494 | 6.7761 | 6.6897 |
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+ | 13.1098 | 15.0 | 195 | 8.7926 | 7.9192 | 1.4133 | 7.742 | 7.6718 |
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+ | 12.4133 | 16.0 | 208 | 8.5472 | 7.0176 | 1.2819 | 6.8465 | 6.8276 |
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+ | 12.4751 | 17.0 | 221 | 8.5494 | 5.918 | 1.0667 | 5.7247 | 5.552 |
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+ | 11.9681 | 18.0 | 234 | 8.5223 | 5.918 | 1.0667 | 5.7247 | 5.552 |
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+ | 11.8797 | 19.0 | 247 | 8.3327 | 5.918 | 1.0667 | 5.7247 | 5.552 |
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+ | 11.8815 | 20.0 | 260 | 8.2775 | 5.918 | 1.0667 | 5.7247 | 5.552 |
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  ### Framework versions
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