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distilbert-base-uncased-classifier

Text Classification
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Safetensors
distilbert
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End of training

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  1. README.md +12 -11
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -19,9 +19,9 @@ 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: 0.3153
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- - Accuracy: 0.8833
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- - F1: 0.7961
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  ## Model description
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@@ -46,17 +46,18 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Use OptimizerNames.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: 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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- | No log | 0 | 0 | 0.6946 | 0.4556 | 0.3792 |
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- | No log | 0.6006 | 188 | 0.3660 | 0.8457 | 0.7207 |
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- | No log | 1.2013 | 376 | 0.3200 | 0.8777 | 0.7692 |
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- | 0.3454 | 1.8019 | 564 | 0.3075 | 0.8801 | 0.7875 |
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- | 0.3454 | 2.4026 | 752 | 0.3209 | 0.8769 | 0.7913 |
 
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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: 0.3636
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+ - Accuracy: 0.8929
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+ - F1: 0.8102
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  ## Model description
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  - seed: 42
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  - optimizer: Use OptimizerNames.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: 5
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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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+ | No log | 0 | 0 | 0.7504 | 0.2894 | 0.4489 |
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+ | No log | 1.0 | 313 | 0.3280 | 0.8697 | 0.7384 |
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+ | 0.3445 | 2.0 | 626 | 0.2999 | 0.8857 | 0.7960 |
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+ | 0.3445 | 3.0 | 939 | 0.3678 | 0.8657 | 0.7846 |
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+ | 0.2115 | 4.0 | 1252 | 0.3471 | 0.8881 | 0.8056 |
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+ | 0.1359 | 5.0 | 1565 | 0.3636 | 0.8929 | 0.8102 |
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  ### Framework versions
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