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End of training

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@@ -13,14 +13,13 @@ model-index:
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/bella05/huggingface/runs/gi9imxak)
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  # pogny-16-0.00002
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  This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.9252
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- - Accuracy: 0.7676
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- - F1: 0.7648
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  ## Model description
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@@ -45,27 +44,20 @@ 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: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
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- | 0.6579 | 1.0 | 4818 | 0.6370 | 0.7627 | 0.7604 |
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- | 0.5424 | 2.0 | 9636 | 0.6263 | 0.7671 | 0.7636 |
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- | 0.4158 | 3.0 | 14454 | 0.6761 | 0.7721 | 0.7690 |
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- | 0.3116 | 4.0 | 19272 | 0.7796 | 0.7705 | 0.7680 |
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- | 0.221 | 5.0 | 24090 | 1.0186 | 0.7640 | 0.7616 |
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- | 0.1605 | 6.0 | 28908 | 1.3264 | 0.7679 | 0.7648 |
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- | 0.122 | 7.0 | 33726 | 1.5300 | 0.7685 | 0.7642 |
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- | 0.0808 | 8.0 | 38544 | 1.7068 | 0.7594 | 0.7574 |
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- | 0.0606 | 9.0 | 43362 | 1.8555 | 0.7632 | 0.7613 |
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- | 0.0249 | 10.0 | 48180 | 1.9252 | 0.7676 | 0.7648 |
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  ### Framework versions
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- - Transformers 4.41.0
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- - Pytorch 2.2.2
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- - Datasets 2.19.1
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- - Tokenizers 0.19.1
 
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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  # pogny-16-0.00002
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  This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.9029
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+ - Accuracy: 0.7647
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+ - F1: 0.7617
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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: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
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+ | 0.1995 | 1.0 | 4818 | 1.4308 | 0.7471 | 0.7452 |
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+ | 0.1231 | 2.0 | 9636 | 1.6541 | 0.7614 | 0.7561 |
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+ | 0.0434 | 3.0 | 14454 | 1.9029 | 0.7647 | 0.7617 |
 
 
 
 
 
 
 
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  ### Framework versions
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+ - Transformers 4.34.1
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+ - Pytorch 2.1.0a0+b5021ba
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+ - Datasets 2.6.2
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+ - Tokenizers 0.14.1