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-cleaned
+  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/bxmx75hr)
+# deberta-finetuned-ner-microsoft-disaster-cleaned
+
+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: 0.0791
+- Precision: 0.9251
+- Recall: 0.9335
+- F1: 0.9292
+- Accuracy: 0.9808
+
+## 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: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0908        | 1.0   | 1799 | 0.0765          | 0.9134    | 0.9236 | 0.9185 | 0.9798   |
+| 0.0668        | 2.0   | 3598 | 0.0735          | 0.9284    | 0.9305 | 0.9295 | 0.9813   |
+| 0.0515        | 3.0   | 5397 | 0.0756          | 0.9231    | 0.9315 | 0.9273 | 0.9804   |
+| 0.0394        | 4.0   | 7196 | 0.0791          | 0.9251    | 0.9335 | 0.9292 | 0.9808   |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.1.2
+- Datasets 2.20.0
+- Tokenizers 0.19.1

runs/Jul27_18-28-14_3f045ee57304/events.out.tfevents.1722104902.3f045ee57304.34.0

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