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denoice-finetuned-xsum

Text2Text Generation
Transformers
Safetensors
t5
Generated from Trainer
text-generation-inference
Inference Endpoints
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  1. README.md +12 -32
  2. model.safetensors +1 -1
  3. 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 [google/t5-efficient-tiny](https://huggingface.co/google/t5-efficient-tiny) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7699
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- - Rouge1: 75.4057
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- - Rouge2: 60.8372
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- - Rougel: 75.2813
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- - Rougelsum: 75.3388
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- - Gen Len: 17.5157
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  ## Model description
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@@ -47,37 +47,17 @@ 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: 25
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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 | 76 | 0.8420 | 72.7754 | 57.4787 | 72.7926 | 72.73 | 17.6387 |
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- | No log | 2.0 | 152 | 0.8339 | 73.0721 | 57.2706 | 73.0236 | 72.9623 | 17.6178 |
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- | No log | 3.0 | 228 | 0.8351 | 73.6099 | 57.967 | 73.5666 | 73.4951 | 17.6623 |
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- | No log | 4.0 | 304 | 0.8239 | 73.5357 | 57.6669 | 73.4526 | 73.5157 | 17.5916 |
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- | No log | 5.0 | 380 | 0.8164 | 73.7228 | 58.0556 | 73.6791 | 73.69 | 17.5969 |
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- | No log | 6.0 | 456 | 0.8133 | 74.1346 | 58.755 | 74.0915 | 74.1094 | 17.6021 |
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- | 1.1888 | 7.0 | 532 | 0.8080 | 74.2063 | 58.7052 | 74.1442 | 74.2247 | 17.5969 |
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- | 1.1888 | 8.0 | 608 | 0.8073 | 74.0301 | 58.5081 | 73.9849 | 74.0378 | 17.5733 |
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- | 1.1888 | 9.0 | 684 | 0.8043 | 74.2651 | 58.8463 | 74.2069 | 74.284 | 17.5785 |
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- | 1.1888 | 10.0 | 760 | 0.8003 | 74.4637 | 59.2146 | 74.4277 | 74.5006 | 17.5838 |
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- | 1.1888 | 11.0 | 836 | 0.7933 | 74.5048 | 59.1095 | 74.4329 | 74.4965 | 17.5707 |
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- | 1.1888 | 12.0 | 912 | 0.7904 | 74.8337 | 59.4889 | 74.7667 | 74.8005 | 17.5733 |
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- | 1.1888 | 13.0 | 988 | 0.7879 | 75.0519 | 59.7797 | 74.937 | 75.0109 | 17.5785 |
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- | 1.1259 | 14.0 | 1064 | 0.7876 | 75.2269 | 60.0994 | 75.1242 | 75.1981 | 17.5628 |
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- | 1.1259 | 15.0 | 1140 | 0.7779 | 75.1229 | 59.887 | 75.0029 | 75.0717 | 17.5445 |
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- | 1.1259 | 16.0 | 1216 | 0.7768 | 75.461 | 60.4297 | 75.255 | 75.3054 | 17.5393 |
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- | 1.1259 | 17.0 | 1292 | 0.7757 | 75.5466 | 60.7191 | 75.397 | 75.4456 | 17.5497 |
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- | 1.1259 | 18.0 | 1368 | 0.7780 | 75.6079 | 60.7743 | 75.4396 | 75.5341 | 17.5497 |
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- | 1.1259 | 19.0 | 1444 | 0.7730 | 75.362 | 60.6829 | 75.1996 | 75.2653 | 17.5393 |
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- | 1.0939 | 20.0 | 1520 | 0.7739 | 75.4207 | 60.7544 | 75.2581 | 75.3047 | 17.5393 |
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- | 1.0939 | 21.0 | 1596 | 0.7730 | 75.363 | 60.7235 | 75.2341 | 75.2882 | 17.5471 |
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- | 1.0939 | 22.0 | 1672 | 0.7713 | 75.3809 | 60.7759 | 75.2489 | 75.3012 | 17.5262 |
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- | 1.0939 | 23.0 | 1748 | 0.7695 | 75.4104 | 60.7961 | 75.2757 | 75.3183 | 17.5157 |
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- | 1.0939 | 24.0 | 1824 | 0.7705 | 75.3482 | 60.8028 | 75.2489 | 75.2857 | 17.5157 |
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- | 1.0939 | 25.0 | 1900 | 0.7699 | 75.4057 | 60.8372 | 75.2813 | 75.3388 | 17.5157 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [google/t5-efficient-tiny](https://huggingface.co/google/t5-efficient-tiny) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7541
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+ - Rouge1: 76.26
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+ - Rouge2: 61.8085
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+ - Rougel: 76.1635
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+ - Rougelsum: 76.1928
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+ - Gen Len: 17.4843
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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: 5
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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 | 76 | 0.7604 | 75.9742 | 61.5113 | 75.8301 | 75.8438 | 17.4817 |
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+ | No log | 2.0 | 152 | 0.7574 | 75.9172 | 61.56 | 75.7901 | 75.8489 | 17.4817 |
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+ | No log | 3.0 | 228 | 0.7568 | 76.382 | 61.5593 | 76.1883 | 76.2735 | 17.4791 |
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+ | No log | 4.0 | 304 | 0.7565 | 76.3074 | 61.8211 | 76.1848 | 76.2148 | 17.4843 |
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+ | No log | 5.0 | 380 | 0.7541 | 76.26 | 61.8085 | 76.1635 | 76.1928 | 17.4843 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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