training and evaluation complete

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: bert-finetuned-ner-football_final
+  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. -->
+
+# bert-finetuned-ner-football_final
+
+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: 0.1473
+- Precision: 0.8997
+- Recall: 0.9311
+- F1: 0.9151
+- Accuracy: 0.9721
+
+## 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 199  | 0.1382          | 0.8850    | 0.9270 | 0.9055 | 0.9701   |
+| No log        | 2.0   | 398  | 0.1359          | 0.9080    | 0.9250 | 0.9164 | 0.9706   |
+| 0.0325        | 3.0   | 597  | 0.1473          | 0.8997    | 0.9311 | 0.9151 | 0.9721   |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.2.2
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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