End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: amazon_review_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. -->
+
+# amazon_review_classification
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3976
+- Accuracy: 0.6732
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 115  | 1.0703          | 0.6732   |
+| No log        | 2.0   | 230  | 1.2393          | 0.6341   |
+| No log        | 3.0   | 345  | 1.1084          | 0.6683   |
+| No log        | 4.0   | 460  | 1.1262          | 0.6829   |
+| 0.3201        | 5.0   | 575  | 1.3179          | 0.6732   |
+| 0.3201        | 6.0   | 690  | 1.3832          | 0.6585   |
+| 0.3201        | 7.0   | 805  | 1.2997          | 0.6683   |
+| 0.3201        | 8.0   | 920  | 1.3872          | 0.6634   |
+| 0.0863        | 9.0   | 1035 | 1.3832          | 0.6634   |
+| 0.0863        | 10.0  | 1150 | 1.3976          | 0.6732   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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