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mt5-small-finetuned-amazon-en-es

Summarization Transformers PyTorch TensorFlow TensorBoard mt5 text2text-generation generated_from_trainer Inference Endpoints text-generation-inference
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  1. README.md +19 -16
  2. pytorch_model.bin +1 -1
  3. runs/Sep29_14-23-20_vorace/1632918487.4283721/events.out.tfevents.1632918487.vorace.2673642.1 +3 -0
  4. runs/Sep29_14-23-20_vorace/events.out.tfevents.1632918487.vorace.2673642.0 +3 -0
  5. runs/Sep29_14-34-02_vorace/1632918914.4980953/events.out.tfevents.1632918914.vorace.2677037.2 +3 -0
  6. runs/Sep29_14-34-02_vorace/events.out.tfevents.1632918892.vorace.2677037.0 +3 -0
  7. runs/Sep29_14-34-02_vorace/events.out.tfevents.1632918914.vorace.2677037.1 +3 -0
  8. tokenizer_config.json +1 -1
  9. training_args.bin +2 -2
README.md CHANGED
@@ -1,6 +1,7 @@
1
  ---
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  license: apache-2.0
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  tags:
 
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  - generated_from_trainer
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  datasets:
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  - null
@@ -15,7 +16,7 @@ model-index:
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  metrics:
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  - name: Rouge1
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  type: rouge
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- value: 10.8752
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -25,12 +26,12 @@ 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 the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.1491
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- - Rouge1: 10.8752
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- - Rouge2: 3.8695
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- - Rougel: 10.6991
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- - Rougelsum: 10.6616
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- - Gen Len: 5.6085
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  ## Model description
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@@ -49,29 +50,31 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-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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- - num_epochs: 6
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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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- | 9.1733 | 1.0 | 2202 | 3.4863 | 6.3629 | 1.4637 | 6.2501 | 6.2752 | 3.3302 |
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- | 4.4547 | 2.0 | 4404 | 3.2809 | 9.1283 | 2.992 | 8.9851 | 9.0487 | 4.7642 |
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- | 4.0581 | 3.0 | 6606 | 3.2108 | 10.5207 | 3.7411 | 10.2595 | 10.234 | 5.3208 |
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- | 3.8821 | 4.0 | 8808 | 3.1701 | 10.8636 | 4.0944 | 10.6462 | 10.6468 | 5.2453 |
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- | 3.7857 | 5.0 | 11010 | 3.1600 | 10.9456 | 4.5187 | 10.784 | 10.7542 | 5.691 |
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- | 3.7273 | 6.0 | 13212 | 3.1491 | 10.8752 | 3.8695 | 10.6991 | 10.6616 | 5.6085 |
 
 
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  ### Framework versions
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  - Transformers 4.10.3
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- - Pytorch 1.9.1+cu102
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  - Datasets 1.12.1
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  - Tokenizers 0.10.3
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  ---
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  license: apache-2.0
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  tags:
4
+ - summarization
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  - generated_from_trainer
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  datasets:
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  - null
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  metrics:
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  - name: Rouge1
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  type: rouge
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+ value: 12.4927
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  ---
21
 
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
26
 
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  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.9894
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+ - Rouge1: 12.4927
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+ - Rouge2: 4.847
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+ - Rougel: 12.4387
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+ - Rougelsum: 12.4383
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+ - Gen Len: 6.1675
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 4e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
56
  - 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 | Gen Len |
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  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
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+ | 6.5619 | 1.0 | 2202 | 3.2749 | 9.2423 | 3.2813 | 9.2013 | 9.1698 | 5.0354 |
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+ | 3.8525 | 2.0 | 4404 | 3.1296 | 11.1883 | 4.047 | 11.1545 | 11.1885 | 6.4033 |
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+ | 3.5419 | 3.0 | 6606 | 3.0478 | 11.4905 | 4.4465 | 11.3538 | 11.3805 | 6.6462 |
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+ | 3.4045 | 4.0 | 8808 | 3.0174 | 11.5798 | 4.4426 | 11.5372 | 11.571 | 6.6816 |
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+ | 3.3091 | 5.0 | 11010 | 3.0080 | 12.0207 | 4.5622 | 11.9232 | 11.9476 | 6.4976 |
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+ | 3.2457 | 6.0 | 13212 | 2.9981 | 12.2459 | 4.6924 | 12.2306 | 12.2375 | 6.1533 |
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+ | 3.2179 | 7.0 | 15414 | 2.9943 | 12.3927 | 4.6072 | 12.2888 | 12.2848 | 6.3561 |
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+ | 3.1898 | 8.0 | 17616 | 2.9894 | 12.4927 | 4.847 | 12.4387 | 12.4383 | 6.1675 |
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  ### Framework versions
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  - Transformers 4.10.3
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+ - Pytorch 1.9.1+cu111
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  - Datasets 1.12.1
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  - Tokenizers 0.10.3
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