Model save

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- imdb
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: distilbert-imdb
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: imdb
+      type: imdb
+      config: plain_text
+      split: test[6250:12500]+test[-12500:-6250]
+      args: plain_text
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.93024
+    - name: F1
+      type: f1
+      value: 0.9302304818748904
+    - name: Precision
+      type: precision
+      value: 0.93047490567909
+    - name: Recall
+      type: recall
+      value: 0.93024
+---
+
+<!-- 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-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: 0.2118
+- Accuracy: 0.9302
+- F1: 0.9302
+- Precision: 0.9305
+- Recall: 0.9302
+
+## 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: 32
+- eval_batch_size: 64
+- seed: 9072
+- 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     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.2803        | 1.0   | 782  | 0.1874          | 0.9276   | 0.9276 | 0.9276    | 0.9276 |
+| 0.1143        | 2.0   | 1564 | 0.2118          | 0.9302   | 0.9302 | 0.9305    | 0.9302 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.1.2
+- Datasets 2.1.0
+- Tokenizers 0.15.2

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