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End of training

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  1. README.md +10 -8
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -16,10 +16,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.2438
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- - Start Accuracy: 0.4667
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- - End Accuracy: 0.4667
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- - Total Accuracy: 0.4667
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  ## Model description
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@@ -44,15 +44,17 @@ 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: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Start Accuracy | End Accuracy | Total Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------------:|:------------:|:--------------:|
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- | 2.0713 | 1.0 | 88 | 2.5005 | 0.385 | 0.4033 | 0.3942 |
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- | 1.6649 | 2.0 | 176 | 2.2952 | 0.4533 | 0.4483 | 0.4508 |
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- | 1.2196 | 3.0 | 264 | 2.2438 | 0.4667 | 0.4667 | 0.4667 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.6976
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+ - Start Accuracy: 0.3233
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+ - End Accuracy: 0.3467
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+ - Total Accuracy: 0.3350
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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: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Start Accuracy | End Accuracy | Total Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------------:|:------------:|:--------------:|
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+ | 3.6709 | 1.0 | 88 | 3.5084 | 0.105 | 0.1233 | 0.1142 |
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+ | 3.2985 | 2.0 | 176 | 3.1792 | 0.1517 | 0.1917 | 0.1717 |
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+ | 2.7692 | 3.0 | 264 | 2.9276 | 0.2233 | 0.2717 | 0.2475 |
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+ | 2.0799 | 4.0 | 352 | 2.7302 | 0.2967 | 0.3317 | 0.3142 |
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+ | 1.9322 | 5.0 | 440 | 2.6976 | 0.3233 | 0.3467 | 0.3350 |
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  ### Framework versions
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