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eliza-dukim
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bert-base-finetuned-ynat

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
2
eliza-dukim commited on
Commit
7f45e1b
·
1 Parent(s): fae88ad

add model

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Files changed (3) hide show
  1. README.md +10 -10
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,7 +18,7 @@ model_index:
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  metric:
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  name: F1
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  type: f1
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- value: 0.8691323654981199
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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
@@ -28,8 +28,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on the klue 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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- - F1: 0.8691
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  ## Model description
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@@ -49,8 +49,8 @@ More information needed
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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: 64
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- - eval_batch_size: 64
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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
@@ -60,11 +60,11 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.4713 | 1.0 | 714 | 0.3839 | 0.8670 |
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- | 0.3157 | 2.0 | 1428 | 0.3636 | 0.8691 |
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- | 0.2153 | 3.0 | 2142 | 0.3837 | 0.8657 |
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- | 0.1839 | 4.0 | 2856 | 0.4168 | 0.8629 |
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- | 0.132 | 5.0 | 3570 | 0.4334 | 0.8680 |
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  ### Framework versions
 
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  metric:
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  name: F1
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  type: f1
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+ value: 0.8699556378491373
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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 [klue/bert-base](https://huggingface.co/klue/bert-base) on the klue dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3741
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+ - F1: 0.8700
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  ## Model description
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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: 256
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+ - eval_batch_size: 256
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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 | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | No log | 1.0 | 179 | 0.4458 | 0.8516 |
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+ | No log | 2.0 | 358 | 0.3741 | 0.8700 |
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+ | 0.385 | 3.0 | 537 | 0.3720 | 0.8693 |
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+ | 0.385 | 4.0 | 716 | 0.3744 | 0.8689 |
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+ | 0.385 | 5.0 | 895 | 0.3801 | 0.8695 |
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  ### Framework versions
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