End of training

README.md

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+---
+license: mit
+base_model: microsoft/deberta-v3-base
+tags:
+- generated_from_trainer
+datasets:
+- ontonotes5
+model-index:
+- name: deberta-v3-base_on5
+  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-v3-base_on5
+
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the ontonotes5 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0598
+- F1-type-match: 0.6780
+- F1-partial: 0.6872
+- F1-strict: 0.6565
+- F1-exact: 0.6729
+
+## 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: 0.0001
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 64
+- 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 | F1-type-match | F1-partial | F1-strict | F1-exact |
+|:-------------:|:-----:|:----:|:---------------:|:-------------:|:----------:|:---------:|:--------:|
+| 0.0738        | 1.0   | 936  | 0.0624          | 0.5568        | 0.5632     | 0.5322    | 0.5479   |
+| 0.0432        | 2.0   | 1873 | 0.0591          | 0.5773        | 0.5848     | 0.5559    | 0.5709   |
+| 0.0289        | 3.0   | 2808 | 0.0598          | 0.6780        | 0.6872     | 0.6565    | 0.6729   |
+
+
+### Framework versions
+
+- Transformers 4.36.0
+- Pytorch 2.0.0
+- Datasets 2.1.0
+- Tokenizers 0.15.0

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