End of training

README.md

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+---
+base_model: choidf/finetuning-sentiment-model-bert-base-25000-samples
+tags:
+- generated_from_trainer
+datasets:
+- imdb
+metrics:
+- accuracy
+- f1
+model-index:
+- name: finetuning-sentiment-model-bert-base-25000-samples
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: imdb
+      type: imdb
+      config: plain_text
+      split: train
+      args: plain_text
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9308
+    - name: F1
+      type: f1
+      value: 0.9325009754194303
+---
+
+<!-- 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. -->
+
+# finetuning-sentiment-model-bert-base-25000-samples
+
+This model is a fine-tuned version of [choidf/finetuning-sentiment-model-bert-base-25000-samples](https://huggingface.co/choidf/finetuning-sentiment-model-bert-base-25000-samples) on the imdb dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5129
+- Accuracy: 0.9308
+- F1: 0.9325
+
+## 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.0535        | 1.0   | 1407 | 0.4188          | 0.9224   | 0.9222 |
+| 0.0324        | 2.0   | 2814 | 0.4382          | 0.928    | 0.9288 |
+| 0.0201        | 3.0   | 4221 | 0.4542          | 0.928    | 0.9308 |
+| 0.0202        | 4.0   | 5628 | 0.4747          | 0.9296   | 0.9321 |
+| 0.0057        | 5.0   | 7035 | 0.5129          | 0.9308   | 0.9325 |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1