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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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Training complete

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  1. README.md +16 -14
  2. pytorch_model.bin +1 -1
  3. tokenizer.json +0 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -2,7 +2,6 @@
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  license: apache-2.0
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  tags:
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  - generated_from_trainer
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- - pipeline:summarization
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  datasets:
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  - null
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  metrics:
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  metrics:
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  - name: Rouge1
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  type: rouge
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- value: 8.8272
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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
@@ -26,12 +25,12 @@ 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: 3.3342
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- - Rouge1: 8.8272
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- - Rouge2: 2.5114
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- - Rougel: 8.6749
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- - Rougelsum: 8.6722
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- - Gen Len: 4.2877
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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: 3
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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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- | 9.4562 | 1.0 | 2202 | 3.5591 | 6.6009 | 1.7239 | 6.5036 | 6.5228 | 3.4434 |
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- | 4.6481 | 2.0 | 4404 | 3.3600 | 7.3535 | 1.9174 | 7.2846 | 7.3053 | 3.809 |
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- | 4.3333 | 3.0 | 6606 | 3.3342 | 8.8272 | 2.5114 | 8.6749 | 8.6722 | 4.2877 |
 
 
 
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  ### Framework versions
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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
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  metrics:
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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
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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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  - 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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