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Training in progress, epoch 1

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  1. README.md +18 -8
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7875
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- - Accuracy: 0.8361
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  ## Model description
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@@ -43,17 +43,27 @@ 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: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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- | 0.4516 | 1.0 | 3272 | 0.4798 | 0.7979 |
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- | 0.3258 | 2.0 | 6544 | 0.4744 | 0.8218 |
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- | 0.217 | 3.0 | 9816 | 0.5014 | 0.8340 |
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- | 0.1633 | 4.0 | 13088 | 0.6027 | 0.8474 |
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- | 0.1122 | 5.0 | 16360 | 0.7875 | 0.8361 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9967
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+ - Accuracy: 0.9032
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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: 15
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.3072 | 1.0 | 5250 | 0.2747 | 0.8940 |
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+ | 0.2381 | 2.0 | 10500 | 0.2871 | 0.8986 |
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+ | 0.1858 | 3.0 | 15750 | 0.3444 | 0.8996 |
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+ | 0.1385 | 4.0 | 21000 | 0.4799 | 0.8937 |
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+ | 0.1057 | 5.0 | 26250 | 0.5324 | 0.8961 |
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+ | 0.0779 | 6.0 | 31500 | 0.6222 | 0.8969 |
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+ | 0.0654 | 7.0 | 36750 | 0.6665 | 0.8968 |
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+ | 0.046 | 8.0 | 42000 | 0.7111 | 0.8989 |
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+ | 0.0384 | 9.0 | 47250 | 0.7815 | 0.8987 |
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+ | 0.0348 | 10.0 | 52500 | 0.8023 | 0.9029 |
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+ | 0.0224 | 11.0 | 57750 | 0.8676 | 0.9011 |
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+ | 0.0172 | 12.0 | 63000 | 0.8881 | 0.8999 |
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+ | 0.0068 | 13.0 | 68250 | 0.9122 | 0.9025 |
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+ | 0.0032 | 14.0 | 73500 | 0.9938 | 0.9005 |
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+ | 0.0071 | 15.0 | 78750 | 0.9967 | 0.9032 |
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  ### Framework versions
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