End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- f1
+model-index:
+- name: distilbert-base-uncased-finetuned-nlp-letters-full_text-degendered-class-weighted
+  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-base-uncased-finetuned-nlp-letters-full_text-degendered-class-weighted
+
+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: 0.0045
+- F1: 0.9964
+
+## 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 | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| No log        | 1.0   | 165  | 0.0091          | 0.9946 |
+| No log        | 2.0   | 330  | 0.0045          | 0.9964 |
+| No log        | 3.0   | 495  | 0.0133          | 0.9964 |
+| 0.0233        | 4.0   | 660  | 0.0169          | 0.9964 |
+| 0.0233        | 5.0   | 825  | 0.0185          | 0.9964 |
+| 0.0233        | 6.0   | 990  | 0.0197          | 0.9964 |
+| 0.0002        | 7.0   | 1155 | 0.0204          | 0.9964 |
+| 0.0002        | 8.0   | 1320 | 0.0209          | 0.9964 |
+| 0.0002        | 9.0   | 1485 | 0.0212          | 0.9964 |
+| 0.0001        | 10.0  | 1650 | 0.0213          | 0.9964 |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

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