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denoice-finetuned-xsum

Text2Text Generation
Transformers
Safetensors
t5
Generated from Trainer
text-generation-inference
Inference Endpoints
Model card Files Community
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  1. README.md +87 -14
  2. model.safetensors +1 -1
  3. tokenizer.json +2 -16
README.md CHANGED
@@ -1,8 +1,10 @@
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  ---
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  license: apache-2.0
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- base_model: t5-small
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  tags:
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  - generated_from_trainer
 
 
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  model-index:
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  - name: denoice-finetuned-xsum
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  results: []
@@ -13,19 +15,14 @@ should probably proofread and complete it, then remove this comment. -->
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  # denoice-finetuned-xsum
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- This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - eval_loss: 0.0119
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- - eval_rouge1: 95.4063
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- - eval_rouge2: 71.6891
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- - eval_rougeL: 95.3513
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- - eval_rougeLsum: 95.339
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- - eval_gen_len: 4.1435
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- - eval_runtime: 0.5683
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- - eval_samples_per_second: 784.751
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- - eval_steps_per_second: 1.76
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- - epoch: 23.0
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- - step: 2047
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  ## Model description
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@@ -50,7 +47,83 @@ 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: 100
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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  ---
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  license: apache-2.0
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+ base_model: google/t5-efficient-tiny
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  tags:
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  - generated_from_trainer
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+ metrics:
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+ - rouge
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  model-index:
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  - name: denoice-finetuned-xsum
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  results: []
 
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  # denoice-finetuned-xsum
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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: 0.0289
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+ - Rouge1: 91.6854
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+ - Rouge2: 69.1011
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+ - Rougel: 91.7603
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+ - Rougelsum: 91.9288
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+ - Gen Len: 5.0843
 
 
 
 
 
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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: 70
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+
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+ ### Training results
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+
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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 | 36 | 0.0428 | 89.4757 | 66.4794 | 89.1948 | 89.3633 | 5.1236 |
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+ | No log | 2.0 | 72 | 0.0420 | 90.0187 | 67.603 | 89.7753 | 89.9157 | 5.1348 |
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+ | No log | 3.0 | 108 | 0.0417 | 90.0187 | 67.603 | 89.7753 | 89.9157 | 5.1348 |
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+ | No log | 4.0 | 144 | 0.0411 | 89.7472 | 67.0412 | 89.5318 | 89.6442 | 5.1348 |
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+ | No log | 5.0 | 180 | 0.0405 | 90.0094 | 67.0412 | 89.8408 | 89.9157 | 5.118 |
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+ | No log | 6.0 | 216 | 0.0400 | 90.1498 | 67.4157 | 90.0187 | 90.0936 | 5.1292 |
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+ | No log | 7.0 | 252 | 0.0396 | 90.4775 | 67.9775 | 90.2809 | 90.3839 | 5.1292 |
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+ | No log | 8.0 | 288 | 0.0392 | 90.4775 | 67.9775 | 90.2809 | 90.3839 | 5.1292 |
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+ | No log | 9.0 | 324 | 0.0389 | 90.4775 | 67.9775 | 90.2809 | 90.3839 | 5.1292 |
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+ | No log | 10.0 | 360 | 0.0384 | 90.4775 | 67.9775 | 90.2809 | 90.3839 | 5.1292 |
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+ | No log | 11.0 | 396 | 0.0378 | 90.7491 | 68.4457 | 90.5337 | 90.6929 | 5.118 |
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+ | No log | 12.0 | 432 | 0.0374 | 90.3464 | 68.4457 | 90.2809 | 90.4682 | 5.118 |
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+ | No log | 13.0 | 468 | 0.0372 | 90.7491 | 68.4457 | 90.5337 | 90.6929 | 5.118 |
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+ | 0.075 | 14.0 | 504 | 0.0365 | 90.8614 | 69.1011 | 90.8614 | 90.9925 | 5.1124 |
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+ | 0.075 | 15.0 | 540 | 0.0363 | 90.8614 | 69.1011 | 90.8614 | 90.9925 | 5.1124 |
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+ | 0.075 | 16.0 | 576 | 0.0359 | 90.8614 | 69.1011 | 90.8614 | 90.9925 | 5.1124 |
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+ | 0.075 | 17.0 | 612 | 0.0355 | 90.8614 | 69.1011 | 90.8614 | 90.9925 | 5.1124 |
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+ | 0.075 | 18.0 | 648 | 0.0354 | 90.8614 | 69.1011 | 90.8614 | 90.9925 | 5.1124 |
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+ | 0.075 | 19.0 | 684 | 0.0352 | 90.8614 | 69.1011 | 90.8614 | 90.9925 | 5.1011 |
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+ | 0.075 | 20.0 | 720 | 0.0350 | 90.8614 | 69.1011 | 90.8614 | 90.9925 | 5.1011 |
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+ | 0.075 | 21.0 | 756 | 0.0347 | 90.8614 | 69.1011 | 90.8614 | 90.9925 | 5.1011 |
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+ | 0.075 | 22.0 | 792 | 0.0343 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.1067 |
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+ | 0.075 | 23.0 | 828 | 0.0340 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.1067 |
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+ | 0.075 | 24.0 | 864 | 0.0335 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.1067 |
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+ | 0.075 | 25.0 | 900 | 0.0333 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.1067 |
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+ | 0.075 | 26.0 | 936 | 0.0332 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.1067 |
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+ | 0.075 | 27.0 | 972 | 0.0328 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.1067 |
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+ | 0.0645 | 28.0 | 1008 | 0.0327 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.1067 |
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+ | 0.0645 | 29.0 | 1044 | 0.0324 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.1067 |
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+ | 0.0645 | 30.0 | 1080 | 0.0325 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.1067 |
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+ | 0.0645 | 31.0 | 1116 | 0.0322 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.1067 |
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+ | 0.0645 | 32.0 | 1152 | 0.0321 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.1067 |
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+ | 0.0645 | 33.0 | 1188 | 0.0319 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.1067 |
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+ | 0.0645 | 34.0 | 1224 | 0.0317 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.1067 |
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+ | 0.0645 | 35.0 | 1260 | 0.0316 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.1067 |
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+ | 0.0645 | 36.0 | 1296 | 0.0315 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.0955 |
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+ | 0.0645 | 37.0 | 1332 | 0.0313 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.0955 |
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+ | 0.0645 | 38.0 | 1368 | 0.0312 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.0955 |
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+ | 0.0645 | 39.0 | 1404 | 0.0311 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.0955 |
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+ | 0.0645 | 40.0 | 1440 | 0.0309 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.0955 |
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+ | 0.0645 | 41.0 | 1476 | 0.0307 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.0955 |
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+ | 0.0583 | 42.0 | 1512 | 0.0305 | 90.7303 | 68.867 | 90.7678 | 90.8708 | 5.0955 |
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+ | 0.0583 | 43.0 | 1548 | 0.0304 | 91.2547 | 68.867 | 91.236 | 91.4794 | 5.0955 |
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+ | 0.0583 | 44.0 | 1584 | 0.0305 | 91.2547 | 68.867 | 91.236 | 91.4794 | 5.0955 |
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+ | 0.0583 | 45.0 | 1620 | 0.0304 | 91.4888 | 68.867 | 91.5356 | 91.7603 | 5.0843 |
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+ | 0.0583 | 46.0 | 1656 | 0.0302 | 91.4888 | 68.867 | 91.5356 | 91.7603 | 5.0843 |
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+ | 0.0583 | 47.0 | 1692 | 0.0300 | 91.4888 | 68.867 | 91.5356 | 91.7603 | 5.0843 |
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+ | 0.0583 | 48.0 | 1728 | 0.0300 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0583 | 49.0 | 1764 | 0.0298 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0583 | 50.0 | 1800 | 0.0297 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0583 | 51.0 | 1836 | 0.0296 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0583 | 52.0 | 1872 | 0.0296 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0583 | 53.0 | 1908 | 0.0295 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0583 | 54.0 | 1944 | 0.0295 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0583 | 55.0 | 1980 | 0.0294 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0548 | 56.0 | 2016 | 0.0294 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0548 | 57.0 | 2052 | 0.0293 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0787 |
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+ | 0.0548 | 58.0 | 2088 | 0.0292 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0787 |
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+ | 0.0548 | 59.0 | 2124 | 0.0292 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0548 | 60.0 | 2160 | 0.0291 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0548 | 61.0 | 2196 | 0.0291 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0548 | 62.0 | 2232 | 0.0291 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0548 | 63.0 | 2268 | 0.0290 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0548 | 64.0 | 2304 | 0.0290 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0548 | 65.0 | 2340 | 0.0290 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0548 | 66.0 | 2376 | 0.0289 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0548 | 67.0 | 2412 | 0.0289 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0548 | 68.0 | 2448 | 0.0289 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0548 | 69.0 | 2484 | 0.0289 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+ | 0.0527 | 70.0 | 2520 | 0.0289 | 91.6854 | 69.1011 | 91.7603 | 91.9288 | 5.0843 |
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+
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  ### Framework versions
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model.safetensors CHANGED
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