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update model card README.md

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@@ -14,7 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.0269
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  ## Model description
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@@ -39,41 +39,18 @@ 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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- - lr_scheduler_warmup_steps: 280
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  - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | No log | 0.11 | 100 | 2.7142 |
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- | No log | 0.21 | 200 | 2.4752 |
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- | No log | 0.32 | 300 | 2.3674 |
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- | No log | 0.42 | 400 | 2.3177 |
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- | 2.9171 | 0.53 | 500 | 2.2626 |
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- | 2.9171 | 0.63 | 600 | 2.2268 |
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- | 2.9171 | 0.74 | 700 | 2.2035 |
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- | 2.9171 | 0.84 | 800 | 2.1836 |
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- | 2.9171 | 0.95 | 900 | 2.1626 |
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- | 2.5537 | 1.05 | 1000 | 2.1444 |
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- | 2.5537 | 1.16 | 1100 | 2.1314 |
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- | 2.5537 | 1.26 | 1200 | 2.1192 |
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- | 2.5537 | 1.37 | 1300 | 2.1096 |
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- | 2.5537 | 1.47 | 1400 | 2.0968 |
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- | 2.4399 | 1.58 | 1500 | 2.0868 |
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- | 2.4399 | 1.68 | 1600 | 2.0765 |
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- | 2.4399 | 1.79 | 1700 | 2.0675 |
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- | 2.4399 | 1.89 | 1800 | 2.0606 |
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- | 2.4399 | 2.0 | 1900 | 2.0556 |
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- | 2.4006 | 2.1 | 2000 | 2.0491 |
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- | 2.4006 | 2.21 | 2100 | 2.0454 |
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- | 2.4006 | 2.31 | 2200 | 2.0389 |
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- | 2.4006 | 2.42 | 2300 | 2.0372 |
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- | 2.4006 | 2.52 | 2400 | 2.0326 |
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- | 2.3532 | 2.63 | 2500 | 2.0316 |
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- | 2.3532 | 2.73 | 2600 | 2.0286 |
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- | 2.3532 | 2.84 | 2700 | 2.0276 |
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- | 2.3532 | 2.94 | 2800 | 2.0269 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.0345
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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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+ - lr_scheduler_warmup_steps: 500
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  - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 3.0017 | 0.53 | 500 | 2.3115 |
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+ | 2.5821 | 1.05 | 1000 | 2.1626 |
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+ | 2.4551 | 1.58 | 1500 | 2.0962 |
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+ | 2.4095 | 2.1 | 2000 | 2.0540 |
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+ | 2.3576 | 2.63 | 2500 | 2.0345 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions