Model save

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- emotion
+metrics:
+- accuracy
+model-index:
+- name: pp_distilbert_ft_emotions
+  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: 0.9275
+---
+
+<!-- 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. -->
+
+# pp_distilbert_ft_emotions
+
+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: 0.1493
+- Accuracy: 0.9275
+
+## 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: 5e-05
+- train_batch_size: 80
+- eval_batch_size: 80
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 0.25  | 50   | 0.7329          | 0.758    |
+| No log        | 0.5   | 100  | 0.2915          | 0.9195   |
+| No log        | 0.75  | 150  | 0.2150          | 0.927    |
+| No log        | 1.0   | 200  | 0.1780          | 0.9285   |
+| No log        | 1.25  | 250  | 0.1777          | 0.9295   |
+| No log        | 1.5   | 300  | 0.1547          | 0.937    |
+| No log        | 1.75  | 350  | 0.1467          | 0.935    |
+| No log        | 2.0   | 400  | 0.1446          | 0.937    |
+| No log        | 2.25  | 450  | 0.1482          | 0.934    |
+| 0.3073        | 2.5   | 500  | 0.1335          | 0.9385   |
+| 0.3073        | 2.75  | 550  | 0.1344          | 0.9415   |
+| 0.3073        | 3.0   | 600  | 0.1229          | 0.9425   |
+| 0.3073        | 3.25  | 650  | 0.1381          | 0.939    |
+| 0.3073        | 3.5   | 700  | 0.1292          | 0.941    |
+| 0.3073        | 3.75  | 750  | 0.1278          | 0.944    |
+| 0.3073        | 4.0   | 800  | 0.1258          | 0.944    |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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