Training completed!

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- emotion
+metrics:
+- accuracy
+- f1
+model-index:
+- name: distilbert-base-uncased-finetuned-emotion
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: emotion
+      type: emotion
+      config: split
+      split: validation
+      args: split
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.94
+    - name: F1
+      type: f1
+      value: 0.9399138482178033
+---
+
+<!-- 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 emotion dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2319
+- Accuracy: 0.94
+- F1: 0.9399
+
+## 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: 256
+- eval_batch_size: 256
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| No log        | 1.0   | 63   | 0.1858          | 0.9375   | 0.9373 |
+| No log        | 2.0   | 126  | 0.2010          | 0.9295   | 0.9300 |
+| No log        | 3.0   | 189  | 0.1832          | 0.936    | 0.9365 |
+| 0.0589        | 4.0   | 252  | 0.1928          | 0.9345   | 0.9340 |
+| 0.0589        | 5.0   | 315  | 0.2094          | 0.937    | 0.9367 |
+| 0.0589        | 6.0   | 378  | 0.2016          | 0.937    | 0.9369 |
+| 0.0589        | 7.0   | 441  | 0.2205          | 0.936    | 0.9354 |
+| 0.0427        | 8.0   | 504  | 0.2143          | 0.936    | 0.9355 |
+| 0.0427        | 9.0   | 567  | 0.2184          | 0.9355   | 0.9357 |
+| 0.0427        | 10.0  | 630  | 0.2216          | 0.9365   | 0.9365 |
+| 0.0427        | 11.0  | 693  | 0.2313          | 0.938    | 0.9380 |
+| 0.0261        | 12.0  | 756  | 0.2311          | 0.9395   | 0.9394 |
+| 0.0261        | 13.0  | 819  | 0.2274          | 0.9395   | 0.9394 |
+| 0.0261        | 14.0  | 882  | 0.2302          | 0.9395   | 0.9395 |
+| 0.0261        | 15.0  | 945  | 0.2319          | 0.94     | 0.9399 |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu121
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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