Training complete

README.md

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+---
+license: mit
+base_model: microsoft/deberta-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: deberta-finetuned-ner-microsoft-disaster
+  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. -->
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/akku/huggingface/runs/bxwrwawl)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/akku/huggingface/runs/bxwrwawl)
+# deberta-finetuned-ner-microsoft-disaster
+
+This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1013
+- Precision: 0.9216
+- Recall: 0.9314
+- F1: 0.9265
+- Accuracy: 0.9805
+
+## 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: 7
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0872        | 1.0   | 1799  | 0.0762          | 0.9101    | 0.9245 | 0.9172 | 0.9796   |
+| 0.0658        | 2.0   | 3598  | 0.0741          | 0.9244    | 0.9288 | 0.9266 | 0.9811   |
+| 0.0517        | 3.0   | 5397  | 0.0737          | 0.9282    | 0.9291 | 0.9287 | 0.9808   |
+| 0.0383        | 4.0   | 7196  | 0.0834          | 0.9263    | 0.9275 | 0.9269 | 0.9807   |
+| 0.0298        | 5.0   | 8995  | 0.0895          | 0.9220    | 0.9299 | 0.9259 | 0.9802   |
+| 0.0237        | 6.0   | 10794 | 0.0963          | 0.9203    | 0.9322 | 0.9262 | 0.9806   |
+| 0.0182        | 7.0   | 12593 | 0.1013          | 0.9216    | 0.9314 | 0.9265 | 0.9805   |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.1.2
+- Datasets 2.20.0
+- Tokenizers 0.19.1

runs/Jul24_18-43-14_19a0ded28536/events.out.tfevents.1721847036.19a0ded28536.34.1

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