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End of training

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  1. README.md +20 -14
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0761
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  ## Model description
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@@ -41,24 +41,30 @@ The following hyperparameters were used during training:
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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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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 4
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 1.4592 | 0.32 | 200 | 0.2723 |
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- | 0.2422 | 0.63 | 400 | 0.1839 |
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- | 0.1823 | 0.95 | 600 | 0.1460 |
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- | 0.1348 | 1.26 | 800 | 0.1322 |
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- | 0.1181 | 1.58 | 1000 | 0.1089 |
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- | 0.1047 | 1.9 | 1200 | 0.1064 |
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- | 0.0835 | 2.21 | 1400 | 0.0928 |
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- | 0.0685 | 2.53 | 1600 | 0.0909 |
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- | 0.0614 | 2.84 | 1800 | 0.0873 |
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- | 0.0518 | 3.16 | 2000 | 0.0731 |
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- | 0.0418 | 3.48 | 2200 | 0.0733 |
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- | 0.0449 | 3.79 | 2400 | 0.0761 |
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0404
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  ## Model description
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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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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 6
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.6928 | 0.32 | 200 | 0.2892 |
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+ | 0.2913 | 0.63 | 400 | 0.1697 |
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+ | 0.2028 | 0.95 | 600 | 0.1296 |
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+ | 0.1448 | 1.26 | 800 | 0.1183 |
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+ | 0.1275 | 1.58 | 1000 | 0.1028 |
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+ | 0.11 | 1.9 | 1200 | 0.0827 |
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+ | 0.0821 | 2.21 | 1400 | 0.0754 |
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+ | 0.069 | 2.53 | 1600 | 0.0758 |
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+ | 0.0685 | 2.84 | 1800 | 0.0598 |
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+ | 0.0517 | 3.16 | 2000 | 0.0682 |
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+ | 0.0427 | 3.48 | 2200 | 0.0526 |
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+ | 0.0414 | 3.79 | 2400 | 0.0498 |
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+ | 0.0326 | 4.11 | 2600 | 0.0479 |
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+ | 0.0325 | 4.42 | 2800 | 0.0423 |
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+ | 0.0236 | 4.74 | 3000 | 0.0481 |
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+ | 0.0264 | 5.06 | 3200 | 0.0416 |
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+ | 0.024 | 5.37 | 3400 | 0.0401 |
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+ | 0.0164 | 5.69 | 3600 | 0.0404 |
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  ### Framework versions
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