End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert/distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: distilbert-base-uncased-finetuned-FiNER
+  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-FiNER
+
+This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0336
+- Precision: 0.9154
+- Recall: 0.9327
+- F1: 0.9240
+- Accuracy: 0.9917
+
+## 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: 6
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0354        | 1.0   | 1773  | 0.0375          | 0.8639    | 0.8993 | 0.8812 | 0.9870   |
+| 0.0242        | 2.0   | 3546  | 0.0296          | 0.8929    | 0.9159 | 0.9042 | 0.9895   |
+| 0.0166        | 3.0   | 5319  | 0.0297          | 0.9079    | 0.9208 | 0.9143 | 0.9907   |
+| 0.0117        | 4.0   | 7092  | 0.0303          | 0.9101    | 0.9293 | 0.9196 | 0.9913   |
+| 0.0086        | 5.0   | 8865  | 0.0328          | 0.9065    | 0.9331 | 0.9196 | 0.9913   |
+| 0.0062        | 6.0   | 10638 | 0.0336          | 0.9154    | 0.9327 | 0.9240 | 0.9917   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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