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Krylova
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mt5-small-finetuned-amazon-en-de

Text2Text Generation
Transformers
PyTorch
mt5
Generated from Trainer
Inference Endpoints
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Krylova/m5tsmall

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  1. README.md +16 -12
  2. pytorch_model.bin +1 -1
  3. 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-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.6546
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- - Rouge1: 18.2986
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- - Rouge2: 10.9624
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- - Rougel: 17.8943
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- - Rougelsum: 18.0009
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  ## Model description
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@@ -46,16 +46,20 @@ 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: 4
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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- |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
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- | 3.3465 | 1.0 | 1301 | 2.7467 | 16.9837 | 10.688 | 16.7552 | 16.8412 |
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- | 2.9974 | 2.0 | 2602 | 2.7116 | 17.3625 | 9.9383 | 17.2101 | 17.2771 |
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- | 3.2834 | 3.0 | 3903 | 2.6592 | 17.8403 | 10.7668 | 17.6087 | 17.6695 |
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- | 3.2139 | 4.0 | 5204 | 2.6546 | 18.2986 | 10.9624 | 17.8943 | 18.0009 |
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.5844
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+ - Rouge1: 18.6058
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+ - Rouge2: 10.0803
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+ - Rougel: 18.025
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+ - Rougelsum: 18.2237
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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: 8
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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+ |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
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+ | 2.6887 | 1.0 | 1301 | 2.7862 | 20.3987 | 12.8512 | 19.7713 | 19.7397 |
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+ | 2.5315 | 2.0 | 2602 | 2.7636 | 19.7025 | 11.5086 | 19.2285 | 19.1621 |
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+ | 2.9455 | 3.0 | 3903 | 2.6457 | 20.5245 | 12.445 | 19.9432 | 19.9865 |
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+ | 2.9864 | 4.0 | 5204 | 2.5944 | 19.0345 | 10.3224 | 18.5022 | 18.5792 |
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+ | 2.9746 | 5.0 | 6505 | 2.5910 | 19.5747 | 10.3954 | 18.9401 | 19.1369 |
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+ | 2.9246 | 6.0 | 7806 | 2.5822 | 18.5846 | 9.8889 | 18.0374 | 18.2259 |
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+ | 2.8968 | 7.0 | 9107 | 2.5757 | 18.8335 | 10.2201 | 18.2386 | 18.4522 |
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+ | 2.8645 | 8.0 | 10408 | 2.5844 | 18.6058 | 10.0803 | 18.025 | 18.2237 |
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  ### Framework versions
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