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update model card README.md

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@@ -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 [](https://huggingface.co/) on the generator dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.8383
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  ## Model description
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@@ -41,7 +41,7 @@ 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: cosine
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  - lr_scheduler_warmup_steps: 1000
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- - num_epochs: 120
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  - mixed_precision_training: Native AMP
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  ### Training results
@@ -111,6 +111,38 @@ The following hyperparameters were used during training:
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  | 2.548 | 115.31 | 61000 | 2.8488 |
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  | 2.5468 | 117.2 | 62000 | 2.8412 |
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  | 2.5453 | 119.09 | 63000 | 2.8383 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [](https://huggingface.co/) on the generator dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.4611
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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: cosine
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  - lr_scheduler_warmup_steps: 1000
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+ - num_epochs: 180
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  - mixed_precision_training: Native AMP
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  ### Training results
 
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  | 2.548 | 115.31 | 61000 | 2.8488 |
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  | 2.5468 | 117.2 | 62000 | 2.8412 |
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  | 2.5453 | 119.09 | 63000 | 2.8383 |
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+ | 2.7567 | 120.98 | 64000 | 2.8857 |
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+ | 2.6017 | 122.87 | 65000 | 2.8382 |
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+ | 2.5416 | 124.76 | 66000 | 2.7862 |
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+ | 2.484 | 126.65 | 67000 | 2.7415 |
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+ | 2.4361 | 128.54 | 68000 | 2.7079 |
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+ | 2.3925 | 130.43 | 69000 | 2.6771 |
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+ | 2.3512 | 132.33 | 70000 | 2.6542 |
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+ | 2.3146 | 134.22 | 71000 | 2.6327 |
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+ | 2.2805 | 136.11 | 72000 | 2.6119 |
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+ | 2.2494 | 138.0 | 73000 | 2.5903 |
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+ | 2.2218 | 139.89 | 74000 | 2.5734 |
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+ | 2.1955 | 141.78 | 75000 | 2.5584 |
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+ | 2.1739 | 143.67 | 76000 | 2.5459 |
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+ | 2.154 | 145.56 | 77000 | 2.5337 |
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+ | 2.1324 | 147.45 | 78000 | 2.5260 |
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+ | 2.1149 | 149.34 | 79000 | 2.5169 |
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+ | 2.096 | 151.23 | 80000 | 2.5095 |
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+ | 2.083 | 153.12 | 81000 | 2.5045 |
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+ | 2.0666 | 155.01 | 82000 | 2.4911 |
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+ | 2.0562 | 156.9 | 83000 | 2.4907 |
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+ | 2.0437 | 158.79 | 84000 | 2.4808 |
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+ | 2.0356 | 160.68 | 85000 | 2.4816 |
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+ | 2.0317 | 162.57 | 86000 | 2.4758 |
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+ | 2.0201 | 164.46 | 87000 | 2.4724 |
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+ | 2.0138 | 166.35 | 88000 | 2.4723 |
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+ | 2.0095 | 168.24 | 89000 | 2.4651 |
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+ | 2.0056 | 170.13 | 90000 | 2.4651 |
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+ | 2.0021 | 172.02 | 91000 | 2.4616 |
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+ | 1.9974 | 173.91 | 92000 | 2.4611 |
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+ | 1.9985 | 175.8 | 93000 | 2.4613 |
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+ | 1.9954 | 177.69 | 94000 | 2.4579 |
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+ | 1.9979 | 179.58 | 95000 | 2.4611 |
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  ### Framework versions