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alexbeta80
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mdeberta-v3-base-finetuned-ner

PEFT
Safetensors
deberta-v2
Generated from Trainer
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End of training

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Files changed (6) hide show
  1. README.md +77 -0
  2. adapter_config.json +32 -0
  3. adapter_model.safetensors +3 -0
  4. tokenizer.json +2 -2
  5. tokenizer_config.json +801 -0
  6. training_args.bin +1 -1
README.md ADDED
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+ ---
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+ base_model: microsoft/mdeberta-v3-base
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+ library_name: peft
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+ license: mit
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: mdeberta-v3-base-finetuned-ner
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # mdeberta-v3-base-finetuned-ner
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+
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+ This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1094
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+ - Precision: 0.9101
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+ - Recall: 0.9567
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+ - F1: 0.9328
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+ - Accuracy: 0.9757
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.2289 | 1.0 | 1167 | 0.1496 | 0.8186 | 0.8964 | 0.8557 | 0.9524 |
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+ | 0.1466 | 2.0 | 2334 | 0.1193 | 0.8771 | 0.9312 | 0.9033 | 0.9677 |
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+ | 0.1064 | 3.0 | 3501 | 0.1143 | 0.8768 | 0.9451 | 0.9097 | 0.9673 |
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+ | 0.0808 | 4.0 | 4668 | 0.0978 | 0.8968 | 0.9491 | 0.9222 | 0.9724 |
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+ | 0.0668 | 5.0 | 5835 | 0.1111 | 0.8889 | 0.9533 | 0.9200 | 0.9713 |
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+ | 0.0559 | 6.0 | 7002 | 0.1168 | 0.9054 | 0.9561 | 0.9301 | 0.9746 |
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+ | 0.0459 | 7.0 | 8169 | 0.1085 | 0.9174 | 0.9457 | 0.9313 | 0.9749 |
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+ | 0.0421 | 8.0 | 9336 | 0.1077 | 0.9141 | 0.9516 | 0.9325 | 0.9759 |
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+ | 0.0324 | 9.0 | 10503 | 0.1084 | 0.9148 | 0.9575 | 0.9357 | 0.9766 |
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+ | 0.03 | 10.0 | 11670 | 0.1094 | 0.9101 | 0.9567 | 0.9328 | 0.9757 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
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+ - Transformers 4.42.3
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+ - Pytorch 2.1.2
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
adapter_config.json ADDED
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+ "base_model_name_or_path": "microsoft/mdeberta-v3-base",
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+ "bias": "all",
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+ "inference_mode": true,
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+ "megatron_core": "megatron.core",
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+ "modules_to_save": [
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+ "peft_type": "LORA",
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+ "r": 64,
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+ "use_dora": false,
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