moro01525 commited on
Commit
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1 Parent(s): da70b59

T5 addestrato nella generazione di ricette dopo 2 epoch

Browse files
README.md CHANGED
@@ -1,5 +1,5 @@
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  ---
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- base_model: moro01525/T5_MLM
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  tags:
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  - generated_from_trainer
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  model-index:
@@ -12,9 +12,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # T5_FineTuning
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- This model is a fine-tuned version of [moro01525/T5_MLM](https://huggingface.co/moro01525/T5_MLM) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.9894
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  ## Model description
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@@ -43,13 +43,20 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss |
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- |:-------------:|:-----:|:----:|:---------------:|
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- | 1.3096 | 0.2 | 1500 | 1.0544 |
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- | 1.1176 | 0.4 | 3000 | 1.0182 |
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- | 1.0893 | 0.6 | 4500 | 1.0016 |
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- | 1.0662 | 0.8 | 6000 | 0.9919 |
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- | 1.0432 | 1.0 | 7500 | 0.9894 |
 
 
 
 
 
 
 
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  ### Framework versions
 
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  ---
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+ base_model: moro01525/T5_FineTuning
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  tags:
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  - generated_from_trainer
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  model-index:
 
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  # T5_FineTuning
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+ This model is a fine-tuned version of [moro01525/T5_FineTuning](https://huggingface.co/moro01525/T5_FineTuning) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9083
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:-----:|:---------------:|
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+ | 1.0593 | 0.0780 | 1500 | 0.9724 |
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+ | 1.0372 | 0.1560 | 3000 | 0.9577 |
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+ | 0.9998 | 0.2340 | 4500 | 0.9462 |
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+ | 1.0283 | 0.3120 | 6000 | 0.9380 |
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+ | 0.9937 | 0.3900 | 7500 | 0.9302 |
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+ | 0.9964 | 0.4680 | 9000 | 0.9246 |
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+ | 0.976 | 0.5461 | 10500 | 0.9196 |
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+ | 0.9768 | 0.6241 | 12000 | 0.9158 |
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+ | 0.9591 | 0.7021 | 13500 | 0.9130 |
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+ | 0.9719 | 0.7801 | 15000 | 0.9111 |
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+ | 0.9695 | 0.8581 | 16500 | 0.9096 |
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+ | 0.9774 | 0.9361 | 18000 | 0.9083 |
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  ### Framework versions
config.json CHANGED
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  {
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- "_name_or_path": "moro01525/T5_MLM",
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  "architectures": [
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  "T5ForConditionalGeneration"
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  ],
 
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  {
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  "architectures": [
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  "T5ForConditionalGeneration"
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  ],
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