jjglilleberg commited on
Commit
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Training completed!

Browse files
README.md CHANGED
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  ---
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  license: mit
 
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -16,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1917
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- - F1: 0.8522
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  ## Model description
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@@ -37,28 +38,25 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 4
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- - eval_batch_size: 4
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  - seed: 42
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- - gradient_accumulation_steps: 4
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- - total_train_batch_size: 16
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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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- - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | No log | 1.0 | 1251 | 0.2072 | 0.8084 |
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- | No log | 2.0 | 2502 | 0.1911 | 0.8350 |
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- | No log | 3.0 | 3753 | 0.1917 | 0.8522 |
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  ### Framework versions
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- - Transformers 4.25.1
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- - Pytorch 1.13.0+cu116
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- - Datasets 2.8.0
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- - Tokenizers 0.13.2
 
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  ---
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  license: mit
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+ base_model: xlm-roberta-base
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1758
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+ - F1: 0.8558
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 24
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+ - eval_batch_size: 24
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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 | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.299 | 1.0 | 835 | 0.2074 | 0.8078 |
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+ | 0.1587 | 2.0 | 1670 | 0.1705 | 0.8461 |
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+ | 0.1012 | 3.0 | 2505 | 0.1758 | 0.8558 |
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  ### Framework versions
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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