End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert/distilbert-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: distilBert_cased_for_binary_sentiment_classification
+  results: []
+---
+
+<!-- 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_cased_for_binary_sentiment_classification
+
+This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2352
+- Accuracy: 0.923
+- F1: 0.9199
+
+## 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: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.2856        | 1.0   | 1000 | 0.2463          | 0.913    | 0.9096 |
+| 0.2074        | 2.0   | 2000 | 0.2352          | 0.923    | 0.9199 |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.2.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2