End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: assignment2_attempt10
+  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. -->
+
+# assignment2_attempt10
+
+This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4421
+- Precision: 0.1842
+- Recall: 0.0593
+- F1: 0.0897
+- Accuracy: 0.9385
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 100
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 128  | 0.2825          | 0.3846    | 0.0424 | 0.0763 | 0.9402   |
+| No log        | 2.0   | 256  | 0.2543          | 0.15      | 0.0763 | 0.1011 | 0.9376   |
+| No log        | 3.0   | 384  | 0.3488          | 0.3333    | 0.0847 | 0.1351 | 0.9396   |
+| 0.2284        | 4.0   | 512  | 0.3479          | 0.2857    | 0.1017 | 0.1500 | 0.9393   |
+| 0.2284        | 5.0   | 640  | 0.3368          | 0.1266    | 0.0847 | 0.1015 | 0.9331   |
+| 0.2284        | 6.0   | 768  | 0.4236          | 0.2222    | 0.0678 | 0.1039 | 0.9397   |
+| 0.2284        | 7.0   | 896  | 0.4421          | 0.1842    | 0.0593 | 0.0897 | 0.9385   |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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