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DelaliScratchwerk
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time-period-classifier-bert

Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
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DelaliScratchwerk commited on
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End of training

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  1. README.md +15 -9
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,9 +18,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.7868
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- - Accuracy: 0.25
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- - F1 Macro: 0.1222
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  ## Model description
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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: 32
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  - seed: 42
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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: 4
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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- | No log | 1.0 | 4 | 1.7927 | 0.0833 | 0.0256 |
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- | No log | 2.0 | 8 | 1.7898 | 0.25 | 0.1574 |
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- | No log | 3.0 | 12 | 1.7878 | 0.3333 | 0.1693 |
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- | No log | 4.0 | 16 | 1.7868 | 0.25 | 0.1222 |
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8658
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+ - Accuracy: 0.75
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+ - F1 Macro: 0.6944
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  ## Model description
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  ### Training hyperparameters
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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: 16
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  - eval_batch_size: 32
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  - seed: 42
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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 | Accuracy | F1 Macro |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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+ | No log | 1.0 | 5 | 1.7893 | 0.1667 | 0.0476 |
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+ | No log | 2.0 | 10 | 1.7629 | 0.1667 | 0.0556 |
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+ | No log | 3.0 | 15 | 1.6525 | 0.5833 | 0.4944 |
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+ | No log | 4.0 | 20 | 1.4081 | 0.5833 | 0.55 |
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+ | No log | 5.0 | 25 | 1.2128 | 0.6667 | 0.6175 |
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+ | No log | 6.0 | 30 | 1.0316 | 0.75 | 0.6944 |
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+ | No log | 7.0 | 35 | 0.9538 | 0.75 | 0.6944 |
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+ | No log | 8.0 | 40 | 0.9044 | 0.75 | 0.6944 |
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+ | No log | 9.0 | 45 | 0.8794 | 0.8333 | 0.8333 |
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+ | 1.2379 | 10.0 | 50 | 0.8658 | 0.75 | 0.6944 |
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  ### Framework versions
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