End of training

README.md

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+---
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- f1
+model-index:
+- name: roberta-base-finetuned-nlp-letters-s1_s2-pronouns-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. -->
+
+# roberta-base-finetuned-nlp-letters-s1_s2-pronouns-class-weighted
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9811
+- F1: 0.7930
+
+## 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   | 221  | 0.4770          | 0.4349 |
+| No log        | 2.0   | 442  | 0.4274          | 0.6585 |
+| 0.4682        | 3.0   | 663  | 0.4237          | 0.4813 |
+| 0.4682        | 4.0   | 884  | 0.9811          | 0.7930 |
+| 0.3471        | 5.0   | 1105 | 0.7504          | 0.7712 |
+| 0.3471        | 6.0   | 1326 | 1.0192          | 0.7615 |
+| 0.2611        | 7.0   | 1547 | 1.2847          | 0.7700 |
+| 0.2611        | 8.0   | 1768 | 1.5530          | 0.7729 |
+| 0.2611        | 9.0   | 1989 | 1.4447          | 0.7483 |
+| 0.1835        | 10.0  | 2210 | 1.6960          | 0.7654 |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

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