Model save

README.md

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+---
+license: mit
+base_model: hongpingjun98/BioMedNLP_DeBERTa
+tags:
+- generated_from_trainer
+datasets:
+- sem_eval_2024_task_2
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: BioMedNLP_DeBERTa_all_updates
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: sem_eval_2024_task_2
+      type: sem_eval_2024_task_2
+      config: sem_eval_2024_task_2_source
+      split: validation
+      args: sem_eval_2024_task_2_source
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.655
+    - name: Precision
+      type: precision
+      value: 0.6551396256630968
+    - name: Recall
+      type: recall
+      value: 0.655
+    - name: F1
+      type: f1
+      value: 0.6549223575304444
+---
+
+<!-- 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. -->
+
+# BioMedNLP_DeBERTa_all_updates
+
+This model is a fine-tuned version of [hongpingjun98/BioMedNLP_DeBERTa](https://huggingface.co/hongpingjun98/BioMedNLP_DeBERTa) on the sem_eval_2024_task_2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.5118
+- Accuracy: 0.655
+- Precision: 0.6551
+- Recall: 0.655
+- F1: 0.6549
+
+## 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: 5e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 50
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 9    | 0.6482          | 0.62     | 0.6403    | 0.62   | 0.6058 |
+| 0.7604        | 2.0   | 18   | 0.6376          | 0.635    | 0.6515    | 0.635  | 0.6248 |
+| 0.7485        | 3.0   | 27   | 0.6256          | 0.655    | 0.6672    | 0.655  | 0.6486 |
+| 0.7114        | 4.0   | 36   | 0.6188          | 0.675    | 0.6790    | 0.675  | 0.6732 |
+| 0.6906        | 5.0   | 45   | 0.6181          | 0.705    | 0.7050    | 0.705  | 0.7050 |
+| 0.5355        | 6.0   | 54   | 0.6257          | 0.68     | 0.6803    | 0.6800 | 0.6799 |
+| 0.5411        | 7.0   | 63   | 0.6258          | 0.675    | 0.6754    | 0.675  | 0.6748 |
+| 0.4849        | 8.0   | 72   | 0.6376          | 0.665    | 0.6670    | 0.665  | 0.6640 |
+| 0.4386        | 9.0   | 81   | 0.6507          | 0.68     | 0.6826    | 0.6800 | 0.6788 |
+| 0.3565        | 10.0  | 90   | 0.6631          | 0.685    | 0.6850    | 0.685  | 0.6850 |
+| 0.3565        | 11.0  | 99   | 0.7089          | 0.66     | 0.6616    | 0.6600 | 0.6591 |
+| 0.2992        | 12.0  | 108  | 0.7791          | 0.67     | 0.6717    | 0.6700 | 0.6692 |
+| 0.2092        | 13.0  | 117  | 0.8224          | 0.68     | 0.6803    | 0.6800 | 0.6799 |
+| 0.1643        | 14.0  | 126  | 0.9128          | 0.675    | 0.6750    | 0.675  | 0.6750 |
+| 0.0811        | 15.0  | 135  | 1.0458          | 0.67     | 0.6701    | 0.67   | 0.6700 |
+| 0.0502        | 16.0  | 144  | 1.2061          | 0.67     | 0.6701    | 0.67   | 0.6700 |
+| 0.011         | 17.0  | 153  | 1.3763          | 0.655    | 0.6558    | 0.655  | 0.6546 |
+| 0.0261        | 18.0  | 162  | 1.4862          | 0.655    | 0.6558    | 0.655  | 0.6546 |
+| 0.0057        | 19.0  | 171  | 1.5609          | 0.665    | 0.6651    | 0.665  | 0.6649 |
+| 0.0026        | 20.0  | 180  | 1.6435          | 0.655    | 0.6550    | 0.655  | 0.6550 |
+| 0.0026        | 21.0  | 189  | 1.7122          | 0.655    | 0.6550    | 0.655  | 0.6550 |
+| 0.0019        | 22.0  | 198  | 1.7682          | 0.655    | 0.6550    | 0.655  | 0.6550 |
+| 0.0016        | 23.0  | 207  | 1.8163          | 0.655    | 0.6550    | 0.655  | 0.6550 |
+| 0.0013        | 24.0  | 216  | 1.8590          | 0.655    | 0.6550    | 0.655  | 0.6550 |
+| 0.0012        | 25.0  | 225  | 1.8883          | 0.66     | 0.6601    | 0.66   | 0.6600 |
+| 0.001         | 26.0  | 234  | 1.9199          | 0.665    | 0.6651    | 0.665  | 0.6649 |
+| 0.0008        | 27.0  | 243  | 1.9548          | 0.665    | 0.6651    | 0.665  | 0.6649 |
+| 0.0007        | 28.0  | 252  | 1.9958          | 0.665    | 0.6658    | 0.665  | 0.6646 |
+| 0.0007        | 29.0  | 261  | 2.0427          | 0.665    | 0.6658    | 0.665  | 0.6646 |
+| 0.0006        | 30.0  | 270  | 2.0890          | 0.66     | 0.6601    | 0.66   | 0.6600 |
+| 0.0006        | 31.0  | 279  | 2.1265          | 0.66     | 0.6601    | 0.66   | 0.6600 |
+| 0.0005        | 32.0  | 288  | 2.1537          | 0.66     | 0.6601    | 0.66   | 0.6600 |
+| 0.0077        | 33.0  | 297  | 2.1871          | 0.655    | 0.6550    | 0.655  | 0.6550 |
+| 0.0004        | 34.0  | 306  | 2.2152          | 0.66     | 0.66      | 0.66   | 0.66   |
+| 0.0004        | 35.0  | 315  | 2.2393          | 0.66     | 0.6601    | 0.66   | 0.6600 |
+| 0.0003        | 36.0  | 324  | 2.2641          | 0.66     | 0.6601    | 0.66   | 0.6600 |
+| 0.0003        | 37.0  | 333  | 2.2881          | 0.66     | 0.6601    | 0.66   | 0.6600 |
+| 0.0008        | 38.0  | 342  | 2.3215          | 0.645    | 0.6462    | 0.645  | 0.6443 |
+| 0.0005        | 39.0  | 351  | 2.3445          | 0.665    | 0.6650    | 0.665  | 0.6650 |
+| 0.0426        | 40.0  | 360  | 2.3033          | 0.68     | 0.6818    | 0.6800 | 0.6792 |
+| 0.0426        | 41.0  | 369  | 2.3582          | 0.66     | 0.6601    | 0.66   | 0.6600 |
+| 0.0005        | 42.0  | 378  | 2.3550          | 0.66     | 0.6603    | 0.66   | 0.6599 |
+| 0.0402        | 43.0  | 387  | 2.3575          | 0.665    | 0.6654    | 0.665  | 0.6648 |
+| 0.0003        | 44.0  | 396  | 2.3372          | 0.675    | 0.6752    | 0.675  | 0.6749 |
+| 0.0135        | 45.0  | 405  | 2.3467          | 0.66     | 0.6603    | 0.66   | 0.6599 |
+| 0.0007        | 46.0  | 414  | 2.3033          | 0.685    | 0.6859    | 0.685  | 0.6846 |
+| 0.0003        | 47.0  | 423  | 2.2770          | 0.675    | 0.6764    | 0.675  | 0.6743 |
+| 0.0003        | 48.0  | 432  | 2.3131          | 0.68     | 0.6807    | 0.6800 | 0.6797 |
+| 0.0002        | 49.0  | 441  | 2.4371          | 0.66     | 0.6601    | 0.66   | 0.6600 |
+| 0.0004        | 50.0  | 450  | 2.5118          | 0.655    | 0.6551    | 0.655  | 0.6549 |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0

config.json

@@ -0,0 +1,27 @@
+{
+  "_name_or_path": "hongpingjun98/BioMedNLP_DeBERTa",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.35.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 28895
+}

model.safetensors

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+oid sha256:919e12c6ceff6826eb2fa11610eaa7b2a9ef9bd8045b5313a061ee32db77110f
+size 432960488

special_tokens_map.json

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+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+  "pad_token": {
+    "content": "[PAD]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+  "sep_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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