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phnghiapro
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distilbert-base-uncased-fineturned-clinc

Text Classification
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PyTorch
distilbert
Generated from Trainer
Eval Results
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phnghiapro commited on
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training completed!

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Files changed (3) hide show
  1. README.md +15 -15
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.94
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ 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 clinc_oos dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0266
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- - Accuracy: 0.94
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0004
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- - train_batch_size: 1024
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- - eval_batch_size: 1024
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.0233 | 1.0 | 15 | 0.4949 | 0.5413 |
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- | 0.2713 | 2.0 | 30 | 0.1338 | 0.8471 |
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- | 0.1284 | 3.0 | 45 | 0.0607 | 0.9165 |
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- | 0.0591 | 4.0 | 60 | 0.0407 | 0.9310 |
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- | 0.0487 | 5.0 | 75 | 0.0346 | 0.9358 |
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- | 0.0397 | 6.0 | 90 | 0.0308 | 0.9377 |
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- | 0.0372 | 7.0 | 105 | 0.0287 | 0.9390 |
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- | 0.0345 | 8.0 | 120 | 0.0275 | 0.9406 |
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- | 0.0333 | 9.0 | 135 | 0.0267 | 0.9394 |
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- | 0.0324 | 10.0 | 150 | 0.0266 | 0.94 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9383870967741935
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0292
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+ - Accuracy: 0.9384
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0004
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+ - train_batch_size: 1280
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+ - eval_batch_size: 1280
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.0092 | 1.0 | 12 | 0.6032 | 0.4881 |
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+ | 0.5561 | 2.0 | 24 | 0.2063 | 0.7877 |
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+ | 0.2481 | 3.0 | 36 | 0.0843 | 0.8977 |
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+ | 0.1194 | 4.0 | 48 | 0.0525 | 0.9223 |
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+ | 0.0563 | 5.0 | 60 | 0.0398 | 0.9326 |
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+ | 0.0474 | 6.0 | 72 | 0.0351 | 0.9365 |
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+ | 0.0423 | 7.0 | 84 | 0.0318 | 0.9358 |
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+ | 0.0397 | 8.0 | 96 | 0.0306 | 0.9377 |
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+ | 0.0378 | 9.0 | 108 | 0.0297 | 0.9381 |
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+ | 0.0359 | 10.0 | 120 | 0.0292 | 0.9384 |
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  ### Framework versions
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