Librarian Bot: Add base_model information to model

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- ---
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- license: apache-2.0
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- tags:
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- - generated_from_trainer
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- datasets:
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- - clinc_oos
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- metrics:
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- - accuracy
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- model-index:
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- - name: distilbert-base-uncased-finetuned-clinc
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- results:
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- - task:
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- name: Text Classification
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- type: text-classification
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- dataset:
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- name: clinc_oos
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- type: clinc_oos
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- args: plus
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- metrics:
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- - name: Accuracy
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- type: accuracy
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- value: 0.9170967741935484
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- ---
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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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- should probably proofread and complete it, then remove this comment. -->
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-
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- # distilbert-base-uncased-finetuned-clinc
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-
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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: 0.7778
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- - Accuracy: 0.9171
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-
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- ## Model description
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-
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- More information needed
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-
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- ## Intended uses & limitations
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-
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- More information needed
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-
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- ## Training and evaluation data
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-
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- More information needed
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-
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- ## Training procedure
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-
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- ### Training hyperparameters
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-
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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: 48
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- - eval_batch_size: 48
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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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-
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- ### Training results
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-
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 4.2882 | 1.0 | 318 | 3.2777 | 0.7390 |
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- | 2.6228 | 2.0 | 636 | 1.8739 | 0.8287 |
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- | 1.5439 | 3.0 | 954 | 1.1619 | 0.8894 |
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- | 1.0111 | 4.0 | 1272 | 0.8601 | 0.9094 |
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- | 0.7999 | 5.0 | 1590 | 0.7778 | 0.9171 |
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-
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-
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- ### Framework versions
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-
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- - Transformers 4.11.3
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- - Pytorch 1.12.1+cpu
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- - Datasets 2.4.0
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- - Tokenizers 0.10.3
 
 
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - clinc_oos
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+ metrics:
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+ - accuracy
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+ base_model: distilbert-base-uncased
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+ model-index:
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+ - name: distilbert-base-uncased-finetuned-clinc
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+ results:
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+ - task:
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+ type: text-classification
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+ name: Text Classification
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+ dataset:
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+ name: clinc_oos
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+ type: clinc_oos
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+ args: plus
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+ metrics:
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+ - type: accuracy
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+ value: 0.9170967741935484
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+ name: Accuracy
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+ ---
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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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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # distilbert-base-uncased-finetuned-clinc
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+
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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: 0.7778
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+ - Accuracy: 0.9171
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 48
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+ - eval_batch_size: 48
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 4.2882 | 1.0 | 318 | 3.2777 | 0.7390 |
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+ | 2.6228 | 2.0 | 636 | 1.8739 | 0.8287 |
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+ | 1.5439 | 3.0 | 954 | 1.1619 | 0.8894 |
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+ | 1.0111 | 4.0 | 1272 | 0.8601 | 0.9094 |
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+ | 0.7999 | 5.0 | 1590 | 0.7778 | 0.9171 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.11.3
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+ - Pytorch 1.12.1+cpu
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+ - Datasets 2.4.0
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+ - Tokenizers 0.10.3