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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 commited on
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Krylova/model_name

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  1. README.md +17 -17
  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: 2.5844
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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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  The following hyperparameters were used during training:
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  - learning_rate: 5.6e-05
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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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  ### 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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  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: 2.5620
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+ - Rouge1: 19.3915
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+ - Rouge2: 10.59
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+ - Rougel: 18.7811
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+ - Rougelsum: 18.9784
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5.6e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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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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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
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+ | 2.8704 | 1.0 | 651 | 2.5780 | 17.9954 | 9.8425 | 17.421 | 17.5202 |
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+ | 2.8213 | 2.0 | 1302 | 2.5719 | 18.3944 | 9.9329 | 17.8166 | 17.9457 |
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+ | 2.7672 | 3.0 | 1953 | 2.5643 | 17.4605 | 9.7057 | 16.9978 | 17.0939 |
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+ | 2.7311 | 4.0 | 2604 | 2.5633 | 19.5332 | 11.0145 | 19.0127 | 19.1008 |
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+ | 2.6985 | 5.0 | 3255 | 2.5672 | 19.3155 | 10.1678 | 18.6334 | 18.8022 |
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+ | 2.6644 | 6.0 | 3906 | 2.5589 | 19.3282 | 10.3801 | 18.8039 | 18.9073 |
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+ | 2.654 | 7.0 | 4557 | 2.5540 | 19.2307 | 10.4068 | 18.6708 | 18.896 |
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+ | 2.6318 | 8.0 | 5208 | 2.5620 | 19.3915 | 10.59 | 18.7811 | 18.9784 |
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  ### Framework versions
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