Training Classification task 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-2024-02-10
+  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: 0.747
+    - name: F1
+      type: f1
+      value: 0.6949375855120276
+---
+
+<!-- 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-2024-02-10
+
+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: 0.7689
+- Accuracy: 0.747
+- F1: 0.6949
+
+## 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: 1e-06
+- 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: 9
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 1.331         | 1.0   | 250  | 1.2185          | 0.572    | 0.4495 |
+| 1.1818        | 2.0   | 500  | 1.1132          | 0.5905   | 0.4665 |
+| 1.0888        | 3.0   | 750  | 1.0287          | 0.6235   | 0.5262 |
+| 1.0059        | 4.0   | 1000 | 0.9443          | 0.6905   | 0.6258 |
+| 0.9335        | 5.0   | 1250 | 0.8771          | 0.7135   | 0.6539 |
+| 0.872         | 6.0   | 1500 | 0.8277          | 0.7285   | 0.6726 |
+| 0.8313        | 7.0   | 1750 | 0.7945          | 0.741    | 0.6871 |
+| 0.8047        | 8.0   | 2000 | 0.7757          | 0.747    | 0.6942 |
+| 0.7931        | 9.0   | 2250 | 0.7689          | 0.747    | 0.6949 |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.0
+- Tokenizers 0.15.1

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