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End of training

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  1. README.md +11 -12
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@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [EleutherAI/gpt-neo-125M](https://huggingface.co/EleutherAI/gpt-neo-125M) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 5.4869
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  ## Model description
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@@ -42,22 +42,21 @@ The following hyperparameters were used during training:
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - num_epochs: 10
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- - mixed_precision_training: Native AMP
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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 | 1.0 | 15 | 5.8127 |
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- | No log | 2.0 | 30 | 5.5716 |
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- | No log | 3.0 | 45 | 5.4681 |
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- | No log | 4.0 | 60 | 5.4220 |
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- | No log | 5.0 | 75 | 5.4095 |
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- | No log | 6.0 | 90 | 5.4248 |
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- | No log | 7.0 | 105 | 5.4380 |
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- | No log | 8.0 | 120 | 5.4627 |
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- | No log | 9.0 | 135 | 5.4778 |
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- | No log | 10.0 | 150 | 5.4869 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [EleutherAI/gpt-neo-125M](https://huggingface.co/EleutherAI/gpt-neo-125M) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 6.2957
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  ## Model description
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - num_epochs: 10
 
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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 | 1.0 | 15 | 5.5286 |
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+ | No log | 2.0 | 30 | 5.6499 |
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+ | No log | 3.0 | 45 | 5.7365 |
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+ | No log | 4.0 | 60 | 5.8599 |
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+ | No log | 5.0 | 75 | 5.9417 |
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+ | No log | 6.0 | 90 | 6.0606 |
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+ | No log | 7.0 | 105 | 6.1215 |
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+ | No log | 8.0 | 120 | 6.1976 |
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+ | No log | 9.0 | 135 | 6.2711 |
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+ | No log | 10.0 | 150 | 6.2957 |
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  ### Framework versions