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mT5_base

Text2Text Generation
Transformers
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Safetensors
t5
Generated from Trainer
text-generation-inference
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End of training

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  1. README.md +11 -10
  2. logs/events.out.tfevents.1728140915.56571babd82e.1261.2 +2 -2
README.md CHANGED
@@ -19,12 +19,12 @@ 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: 0.4030
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- - Bleu Score: 45.1405
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- - Precision: 13.3811
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- - Recall: 13.3811
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- - Gen Len: 16.8196
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- - Err: 13.3811
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  ## Model description
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@@ -49,15 +49,16 @@ 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: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Bleu Score | Precision | Recall | Gen Len | Err |
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  |:-------------:|:-----:|:----:|:---------------:|:----------:|:---------:|:-------:|:-------:|:-------:|
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- | 2.8374 | 1.0 | 838 | 0.5595 | 41.3763 | 7.1685 | 7.1685 | 16.7802 | 7.1685 |
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- | 0.7564 | 2.0 | 1676 | 0.4503 | 44.4878 | 12.0669 | 12.0669 | 16.8124 | 12.0669 |
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- | 0.6103 | 3.0 | 2514 | 0.4030 | 45.1405 | 13.3811 | 13.3811 | 16.8196 | 13.3811 |
 
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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 the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3417
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+ - Bleu Score: 47.0526
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+ - Precision: 17.2043
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+ - Recall: 17.2043
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+ - Gen Len: 16.8315
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+ - Err: 17.2043
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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: 4
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Bleu Score | Precision | Recall | Gen Len | Err |
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  |:-------------:|:-----:|:----:|:---------------:|:----------:|:---------:|:-------:|:-------:|:-------:|
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+ | 2.798 | 1.0 | 838 | 0.5495 | 41.8683 | 7.7658 | 7.7658 | 16.7766 | 7.7658 |
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+ | 0.7216 | 2.0 | 1676 | 0.4311 | 44.9002 | 13.0227 | 13.0227 | 16.8148 | 13.0227 |
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+ | 0.5551 | 3.0 | 2514 | 0.3565 | 46.5247 | 16.0096 | 16.0096 | 16.816 | 16.0096 |
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+ | 0.4951 | 4.0 | 3352 | 0.3417 | 47.0526 | 17.2043 | 17.2043 | 16.8315 | 17.2043 |
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  ### Framework versions
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