Emotions dataset finetuned classification

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-cased
+tags:
+- generated_from_trainer
+datasets:
+- emotion
+metrics:
+- accuracy
+- f1
+model-index:
+- name: my-finetuned-emotion-distilbert
+  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: 0.9255
+    - name: F1
+      type: f1
+      value: 0.9253827930853522
+---
+
+<!-- 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. -->
+
+# my-finetuned-emotion-distilbert
+
+This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the emotion dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1875
+- Accuracy: 0.9255
+- F1: 0.9254
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| No log        | 1.0   | 250  | 0.2592          | 0.913    | 0.9134 |
+| No log        | 2.0   | 500  | 0.1875          | 0.9255   | 0.9254 |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

runs/Jun23_06-30-36_fa5c9c99e329/events.out.tfevents.1719125076.fa5c9c99e329.586.0

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