End of training
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README.md
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---
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base_model: old_models/LaBSE/0_Transformer
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tags:
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- generated_from_trainer
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model-index:
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- name: bert_labse-finetuning-unhealthyConv-dropout005-epochs-10
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results: []
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---
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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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# bert_labse-finetuning-unhealthyConv-dropout005-epochs-10
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This model is a fine-tuned version of [old_models/LaBSE/0_Transformer](https://huggingface.co/old_models/LaBSE/0_Transformer) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7820
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- Mse: 0.7820
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- Rmse: 0.8843
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- Mae: 0.4988
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- R2: 0.8587
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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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 | Mse | Rmse | Mae | R2 |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|
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| 1.5159 | 1.0 | 3389 | 1.2618 | 1.2618 | 1.1233 | 0.7882 | 0.7720 |
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| 1.0247 | 2.0 | 6778 | 1.1135 | 1.1135 | 1.0552 | 0.7067 | 0.7988 |
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| 0.7849 | 3.0 | 10167 | 1.1353 | 1.1353 | 1.0655 | 0.7289 | 0.7949 |
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| 0.6271 | 4.0 | 13556 | 0.9255 | 0.9255 | 0.9620 | 0.6331 | 0.8328 |
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| 0.5029 | 5.0 | 16945 | 0.9135 | 0.9135 | 0.9558 | 0.6148 | 0.8349 |
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| 0.3947 | 6.0 | 20334 | 0.8166 | 0.8166 | 0.9036 | 0.5446 | 0.8525 |
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| 0.3264 | 7.0 | 23723 | 0.8280 | 0.8280 | 0.9099 | 0.5552 | 0.8504 |
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| 0.2774 | 8.0 | 27112 | 0.8125 | 0.8125 | 0.9014 | 0.5408 | 0.8532 |
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| 0.2245 | 9.0 | 30501 | 0.7870 | 0.7870 | 0.8871 | 0.5034 | 0.8578 |
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| 0.2028 | 10.0 | 33890 | 0.7820 | 0.7820 | 0.8843 | 0.4988 | 0.8587 |
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### Framework versions
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- Transformers 4.33.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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