End of training

README.md

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+---
+license: mit
+base_model: microsoft/deberta-v3-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: DeBERTa-finetuned-ner-copious
+  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. -->
+
+# DeBERTa-finetuned-ner-copious
+
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0499
+- Precision: 0.7867
+- Recall: 0.8333
+- F1: 0.8094
+- Accuracy: 0.9842
+
+## 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 63   | 0.0632          | 0.6793    | 0.7383 | 0.7076 | 0.9789   |
+| No log        | 2.0   | 126  | 0.0507          | 0.7559    | 0.8320 | 0.7921 | 0.9837   |
+| No log        | 3.0   | 189  | 0.0517          | 0.7771    | 0.8306 | 0.8029 | 0.9840   |
+| No log        | 4.0   | 252  | 0.0517          | 0.7822    | 0.8457 | 0.8127 | 0.9839   |
+| No log        | 5.0   | 315  | 0.0499          | 0.7867    | 0.8333 | 0.8094 | 0.9842   |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3