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scenario-non-kd-scr-ner-full-mdeberta_data-univner_full44

Token Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
Inference Endpoints
Model card Files Community
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  1. README.md +117 -0
  2. config.json +53 -0
  3. eval_result_ner.json +1 -0
  4. model.safetensors +3 -0
  5. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: microsoft/mdeberta-v3-base
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+ tags:
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+ - generated_from_trainer
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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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+ model-index:
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+ - name: scenario-non-kd-scr-ner-full-mdeberta_data-univner_full44
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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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+ # scenario-non-kd-scr-ner-full-mdeberta_data-univner_full44
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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: 0.3159
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+ - Precision: 0.6317
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+ - Recall: 0.6096
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+ - F1: 0.6205
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+ - Accuracy: 0.9636
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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: 3e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 44
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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: 30
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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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+ | 0.3088 | 0.2910 | 500 | 0.2391 | 0.3299 | 0.2154 | 0.2606 | 0.9344 |
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+ | 0.1992 | 0.5821 | 1000 | 0.1901 | 0.3635 | 0.3792 | 0.3712 | 0.9430 |
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+ | 0.1511 | 0.8731 | 1500 | 0.1697 | 0.4865 | 0.4499 | 0.4675 | 0.9520 |
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+ | 0.1103 | 1.1641 | 2000 | 0.1592 | 0.5109 | 0.5203 | 0.5155 | 0.9553 |
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+ | 0.09 | 1.4552 | 2500 | 0.1498 | 0.5337 | 0.5649 | 0.5488 | 0.9578 |
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+ | 0.0852 | 1.7462 | 3000 | 0.1489 | 0.5792 | 0.5224 | 0.5493 | 0.9592 |
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+ | 0.0739 | 2.0373 | 3500 | 0.1468 | 0.5588 | 0.6070 | 0.5819 | 0.9606 |
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+ | 0.0469 | 2.3283 | 4000 | 0.1673 | 0.5990 | 0.5625 | 0.5802 | 0.9612 |
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+ | 0.0479 | 2.6193 | 4500 | 0.1578 | 0.5783 | 0.6139 | 0.5956 | 0.9612 |
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+ | 0.0472 | 2.9104 | 5000 | 0.1568 | 0.6109 | 0.5914 | 0.6010 | 0.9627 |
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+ | 0.0318 | 3.2014 | 5500 | 0.1806 | 0.6092 | 0.5807 | 0.5946 | 0.9622 |
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+ | 0.0271 | 3.4924 | 6000 | 0.1910 | 0.5860 | 0.5659 | 0.5757 | 0.9605 |
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+ | 0.0289 | 3.7835 | 6500 | 0.1811 | 0.5978 | 0.5990 | 0.5984 | 0.9626 |
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+ | 0.0246 | 4.0745 | 7000 | 0.1958 | 0.6135 | 0.6027 | 0.6080 | 0.9630 |
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+ | 0.0165 | 4.3655 | 7500 | 0.2066 | 0.6118 | 0.5927 | 0.6021 | 0.9621 |
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+ | 0.0177 | 4.6566 | 8000 | 0.2033 | 0.5884 | 0.6018 | 0.5950 | 0.9608 |
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+ | 0.0178 | 4.9476 | 8500 | 0.2051 | 0.5985 | 0.5956 | 0.5970 | 0.9620 |
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+ | 0.0117 | 5.2386 | 9000 | 0.2181 | 0.5962 | 0.6174 | 0.6066 | 0.9619 |
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+ | 0.0107 | 5.5297 | 9500 | 0.2247 | 0.5859 | 0.6119 | 0.5986 | 0.9610 |
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+ | 0.013 | 5.8207 | 10000 | 0.2253 | 0.6049 | 0.5825 | 0.5935 | 0.9618 |
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+ | 0.0106 | 6.1118 | 10500 | 0.2280 | 0.6130 | 0.6068 | 0.6099 | 0.9625 |
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+ | 0.0071 | 6.4028 | 11000 | 0.2321 | 0.6006 | 0.6292 | 0.6146 | 0.9623 |
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+ | 0.0077 | 6.6938 | 11500 | 0.2497 | 0.5847 | 0.6024 | 0.5934 | 0.9612 |
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+ | 0.0085 | 6.9849 | 12000 | 0.2421 | 0.5838 | 0.6058 | 0.5946 | 0.9611 |
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+ | 0.0053 | 7.2759 | 12500 | 0.2562 | 0.6189 | 0.5917 | 0.6050 | 0.9627 |
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+ | 0.0057 | 7.5669 | 13000 | 0.2602 | 0.5918 | 0.6138 | 0.6026 | 0.9613 |
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+ | 0.0065 | 7.8580 | 13500 | 0.2531 | 0.6077 | 0.6148 | 0.6112 | 0.9625 |
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+ | 0.0048 | 8.1490 | 14000 | 0.2634 | 0.6182 | 0.6141 | 0.6161 | 0.9628 |
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+ | 0.004 | 8.4400 | 14500 | 0.2736 | 0.6197 | 0.5969 | 0.6081 | 0.9622 |
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+ | 0.0053 | 8.7311 | 15000 | 0.2579 | 0.6194 | 0.6119 | 0.6156 | 0.9633 |
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+ | 0.0042 | 9.0221 | 15500 | 0.2770 | 0.6223 | 0.6211 | 0.6217 | 0.9633 |
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+ | 0.003 | 9.3132 | 16000 | 0.2835 | 0.6010 | 0.6081 | 0.6046 | 0.9622 |
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+ | 0.0031 | 9.6042 | 16500 | 0.2839 | 0.6408 | 0.5954 | 0.6173 | 0.9632 |
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+ | 0.0035 | 9.8952 | 17000 | 0.2876 | 0.6209 | 0.5996 | 0.6101 | 0.9623 |
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+ | 0.0034 | 10.1863 | 17500 | 0.2839 | 0.6215 | 0.6044 | 0.6128 | 0.9628 |
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+ | 0.0026 | 10.4773 | 18000 | 0.2851 | 0.6053 | 0.6187 | 0.6119 | 0.9626 |
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+ | 0.0032 | 10.7683 | 18500 | 0.2799 | 0.6120 | 0.6068 | 0.6094 | 0.9620 |
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+ | 0.003 | 11.0594 | 19000 | 0.2912 | 0.6110 | 0.6306 | 0.6207 | 0.9629 |
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+ | 0.0019 | 11.3504 | 19500 | 0.2963 | 0.6188 | 0.6201 | 0.6194 | 0.9629 |
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+ | 0.0025 | 11.6414 | 20000 | 0.2876 | 0.6101 | 0.6240 | 0.6170 | 0.9628 |
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+ | 0.0023 | 11.9325 | 20500 | 0.2940 | 0.6392 | 0.6001 | 0.6190 | 0.9631 |
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+ | 0.0017 | 12.2235 | 21000 | 0.3056 | 0.6017 | 0.6177 | 0.6096 | 0.9625 |
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+ | 0.0013 | 12.5146 | 21500 | 0.3127 | 0.6128 | 0.6018 | 0.6072 | 0.9628 |
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+ | 0.002 | 12.8056 | 22000 | 0.3052 | 0.6160 | 0.6151 | 0.6156 | 0.9630 |
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+ | 0.0018 | 13.0966 | 22500 | 0.3115 | 0.6279 | 0.5999 | 0.6136 | 0.9629 |
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+ | 0.0015 | 13.3877 | 23000 | 0.3121 | 0.6125 | 0.6155 | 0.6140 | 0.9628 |
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+ | 0.0013 | 13.6787 | 23500 | 0.3203 | 0.6193 | 0.6185 | 0.6189 | 0.9629 |
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+ | 0.0015 | 13.9697 | 24000 | 0.3290 | 0.6329 | 0.6028 | 0.6175 | 0.9629 |
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+ | 0.0012 | 14.2608 | 24500 | 0.3267 | 0.6123 | 0.6194 | 0.6158 | 0.9625 |
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+ | 0.0011 | 14.5518 | 25000 | 0.3191 | 0.6213 | 0.6165 | 0.6189 | 0.9633 |
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+ | 0.0011 | 14.8428 | 25500 | 0.3159 | 0.6317 | 0.6096 | 0.6205 | 0.9636 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.1.1+cu121
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+ - Datasets 2.14.5
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+ - Tokenizers 0.19.1
config.json ADDED
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+ {
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+ "_name_or_path": "microsoft/mdeberta-v3-base",
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+ "architectures": [
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+ "DebertaV2ForTokenClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "LABEL_0",
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+ "1": "LABEL_1",
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+ "2": "LABEL_2",
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+ "3": "LABEL_3",
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+ "4": "LABEL_4",
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+ "5": "LABEL_5",
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+ "6": "LABEL_6"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "LABEL_0": 0,
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+ "LABEL_1": 1,
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+ "LABEL_2": 2,
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+ "LABEL_3": 3,
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+ "LABEL_4": 4,
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+ "LABEL_5": 5,
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+ "LABEL_6": 6
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+ },
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+ "layer_norm_eps": 1e-07,
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+ "max_position_embeddings": 512,
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+ "max_relative_positions": -1,
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+ "model_type": "deberta-v2",
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+ "norm_rel_ebd": "layer_norm",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 6,
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+ "pad_token_id": 0,
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+ "pooler_dropout": 0,
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+ "pooler_hidden_act": "gelu",
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+ "pooler_hidden_size": 768,
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+ "pos_att_type": [
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+ "p2c",
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+ "c2p"
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+ ],
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+ "position_biased_input": false,
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+ "position_buckets": 256,
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+ "relative_attention": true,
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+ "share_att_key": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.44.2",
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+ "type_vocab_size": 0,
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+ "vocab_size": 251000
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+ }
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