End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- imdb
+metrics:
+- accuracy
+- f1
+model-index:
+- name: distilbert-base-uncased-finetuned-imdb
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: imdb
+      type: imdb
+      config: plain_text
+      split: test
+      args: plain_text
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value:
+        accuracy: 0.93192
+    - name: F1
+      type: f1
+      value:
+        f1: 0.9319183250818663
+---
+
+<!-- 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-imdb
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2776
+- Accuracy: {'accuracy': 0.93192}
+- F1: {'f1': 0.9319183250818663}
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy              | F1                         |
+|:-------------:|:-----:|:----:|:---------------:|:---------------------:|:--------------------------:|
+| 0.227         | 1.0   | 1563 | 0.2893          | {'accuracy': 0.89856} | {'f1': 0.8979731717204342} |
+| 0.16          | 2.0   | 3126 | 0.2327          | {'accuracy': 0.92876} | {'f1': 0.9287230772995674} |
+| 0.0914        | 3.0   | 4689 | 0.2776          | {'accuracy': 0.93192} | {'f1': 0.9319183250818663} |
+
+
+### Framework versions
+
+- Transformers 4.33.1
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

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