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README.md

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----
-license: apache-2.0
-tags:
-- generated_from_trainer
-datasets:
-- emotion
-metrics:
-- accuracy
-model-index:
-- name: sagemaker-distilbert-emotion
-  results:
-  - task:
-      type: text-classification
-      name: Text Classification
-    dataset:
-      name: emotion
-      type: emotion
-      args: default
-    metrics:
-    - type: accuracy
-      value: 0.921
-      name: Accuracy
-  - task:
-      type: text-classification
-      name: Text Classification
-    dataset:
-      name: emotion
-      type: emotion
-      config: default
-      split: test
-    metrics:
-    - type: accuracy
-      value: 0.921
-      name: Accuracy
-      verified: true
-      verifyToken: >-
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-    - type: precision
-      value: 0.8870419502496194
-      name: Precision Macro
-      verified: true
-      verifyToken: >-
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-    - type: precision
-      value: 0.921
-      name: Precision Micro
-      verified: true
-      verifyToken: >-
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-    - type: precision
-      value: 0.9208079974712109
-      name: Precision Weighted
-      verified: true
-      verifyToken: >-
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-    - type: recall
-      value: 0.8688429370077566
-      name: Recall Macro
-      verified: true
-      verifyToken: >-
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-    - type: recall
-      value: 0.921
-      name: Recall Micro
-      verified: true
-      verifyToken: >-
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-    - type: recall
-      value: 0.921
-      name: Recall Weighted
-      verified: true
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-    - type: f1
-      value: 0.87642650638535
-      name: F1 Macro
-      verified: true
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-    - type: f1
-      value: 0.9209999999999999
-      name: F1 Micro
-      verified: true
-      verifyToken: >-
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-    - type: loss
-      value: 0.23216550052165985
-      name: loss
-      verified: true
-      verifyToken: >-
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-duplicated_from: lewtun/sagemaker-distilbert-emotion
----
-
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
-# sagemaker-distilbert-emotion
-
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.2322
-- Accuracy: 0.921
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 3e-05
-- train_batch_size: 32
-- eval_batch_size: 64
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 500
-- num_epochs: 1
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.9306        | 1.0   | 500  | 0.2322          | 0.921    |
-
-
-### Framework versions
-
-- Transformers 4.12.3
-- Pytorch 1.9.1
-- Datasets 1.15.1
-- Tokenizers 0.10.3