Training completed!

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- yelp_review_full
+metrics:
+- accuracy
+- f1
+model-index:
+- name: distilbert-base-uncased-finetuned-emotion
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: yelp_review_full
+      type: yelp_review_full
+      config: yelp_review_full
+      split: test
+      args: yelp_review_full
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.564
+    - name: F1
+      type: f1
+      value: 0.5645870203957494
+---
+
+<!-- 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. -->
+
+# distilbert-base-uncased-finetuned-emotion
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the yelp_review_full dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.7507
+- Accuracy: 0.564
+- F1: 0.5646
+
+## 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: 2e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
+| 0.6971        | 1.0   | 1625  | 1.2672          | 0.57     | 0.5725 |
+| 0.6236        | 2.0   | 3250  | 1.4192          | 0.546    | 0.5465 |
+| 0.5152        | 3.0   | 4875  | 2.2110          | 0.556    | 0.5514 |
+| 0.3756        | 4.0   | 6500  | 2.7943          | 0.528    | 0.5232 |
+| 0.2696        | 5.0   | 8125  | 3.0878          | 0.552    | 0.5529 |
+| 0.1722        | 6.0   | 9750  | 3.1261          | 0.564    | 0.5608 |
+| 0.1138        | 7.0   | 11375 | 3.4324          | 0.576    | 0.5769 |
+| 0.0814        | 8.0   | 13000 | 3.6260          | 0.578    | 0.5785 |
+| 0.058         | 9.0   | 14625 | 3.7507          | 0.564    | 0.5628 |
+| 0.0337        | 10.0  | 16250 | 3.7507          | 0.564    | 0.5646 |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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