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  1. README.md +29 -19
  2. runs/Oct19_16-03-32_user/events.out.tfevents.1729334013.user.4063147.0 +2 -2
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 [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.0659
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- - Rouge1: 0.3077
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- - Rouge2: 0.0523
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- - Rougel: 0.2373
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- - Rougelsum: 0.2375
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- - Gen Len: 50.2144
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0002
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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: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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- | 2.7905 | 1.0 | 800 | 2.2300 | 0.1838 | 0.0234 | 0.1522 | 0.1525 | 58.5994 |
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- | 2.3488 | 2.0 | 1600 | 2.1395 | 0.2251 | 0.0339 | 0.1816 | 0.182 | 61.4869 |
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- | 2.2336 | 3.0 | 2400 | 2.1009 | 0.2553 | 0.0406 | 0.2052 | 0.2053 | 56.9838 |
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- | 2.1005 | 4.0 | 3200 | 2.0684 | 0.2777 | 0.0452 | 0.2161 | 0.2163 | 54.5738 |
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- | 2.0007 | 5.0 | 4000 | 2.0559 | 0.2907 | 0.0463 | 0.2247 | 0.2248 | 54.0806 |
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- | 1.9248 | 6.0 | 4800 | 2.0623 | 0.2981 | 0.0475 | 0.2306 | 0.2308 | 50.3856 |
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- | 1.8686 | 7.0 | 5600 | 2.0513 | 0.3013 | 0.0508 | 0.2326 | 0.2327 | 53.965 |
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- | 1.831 | 8.0 | 6400 | 2.0531 | 0.3083 | 0.0517 | 0.2355 | 0.2357 | 51.4162 |
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- | 1.7752 | 9.0 | 7200 | 2.0623 | 0.3022 | 0.0514 | 0.2326 | 0.2329 | 51.6419 |
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- | 1.7515 | 10.0 | 8000 | 2.0659 | 0.3077 | 0.0523 | 0.2373 | 0.2375 | 50.2144 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.1303
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+ - Rouge1: 0.3216
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+ - Rouge2: 0.0621
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+ - Rougel: 0.2469
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+ - Rougelsum: 0.2469
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+ - Gen Len: 48.8488
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0002
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+ - train_batch_size: 16
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+ - eval_batch_size: 12
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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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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+ | No log | 1.0 | 400 | 2.2490 | 0.1594 | 0.0161 | 0.1319 | 0.1321 | 69.2094 |
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+ | 2.7083 | 2.0 | 800 | 2.1665 | 0.2025 | 0.0287 | 0.1648 | 0.1647 | 69.5888 |
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+ | 2.369 | 3.0 | 1200 | 2.1296 | 0.2381 | 0.0344 | 0.1878 | 0.1878 | 57.9775 |
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+ | 2.2185 | 4.0 | 1600 | 2.0890 | 0.2525 | 0.0399 | 0.1986 | 0.1984 | 60.2588 |
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+ | 2.1014 | 5.0 | 2000 | 2.0731 | 0.2795 | 0.0484 | 0.2199 | 0.2199 | 49.5737 |
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+ | 2.1014 | 6.0 | 2400 | 2.0601 | 0.2862 | 0.0525 | 0.2249 | 0.2246 | 54.4206 |
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+ | 1.9992 | 7.0 | 2800 | 2.0592 | 0.3004 | 0.0533 | 0.2351 | 0.2351 | 49.9325 |
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+ | 1.9232 | 8.0 | 3200 | 2.0529 | 0.3033 | 0.0558 | 0.2366 | 0.2368 | 49.8744 |
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+ | 1.8534 | 9.0 | 3600 | 2.0600 | 0.3024 | 0.0573 | 0.2366 | 0.2366 | 50.355 |
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+ | 1.795 | 10.0 | 4000 | 2.0715 | 0.3082 | 0.0561 | 0.2392 | 0.2392 | 47.2162 |
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+ | 1.795 | 11.0 | 4400 | 2.0657 | 0.3137 | 0.0595 | 0.2437 | 0.2439 | 50.3438 |
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+ | 1.73 | 12.0 | 4800 | 2.0759 | 0.3142 | 0.0597 | 0.2434 | 0.2433 | 51.1619 |
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+ | 1.6844 | 13.0 | 5200 | 2.0818 | 0.3172 | 0.0605 | 0.2458 | 0.2458 | 48.9956 |
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+ | 1.6398 | 14.0 | 5600 | 2.0942 | 0.3149 | 0.0599 | 0.2428 | 0.243 | 47.3812 |
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+ | 1.6063 | 15.0 | 6000 | 2.1047 | 0.3171 | 0.0609 | 0.243 | 0.243 | 51.685 |
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+ | 1.6063 | 16.0 | 6400 | 2.1095 | 0.3234 | 0.0622 | 0.248 | 0.248 | 50.1588 |
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+ | 1.5659 | 17.0 | 6800 | 2.1180 | 0.3212 | 0.0627 | 0.2479 | 0.2478 | 49.0894 |
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+ | 1.5456 | 18.0 | 7200 | 2.1212 | 0.3208 | 0.0616 | 0.2455 | 0.2456 | 48.8688 |
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+ | 1.5177 | 19.0 | 7600 | 2.1275 | 0.3214 | 0.0628 | 0.2467 | 0.2467 | 48.4125 |
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+ | 1.5161 | 20.0 | 8000 | 2.1303 | 0.3216 | 0.0621 | 0.2469 | 0.2469 | 48.8488 |
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  ### Framework versions
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