metacognitive_strategy_cls

README.md

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+---
+license: mit
+base_model: microsoft/deberta-v3-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: training1
+  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. -->
+
+# training1
+
+This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1739
+- Accuracy: 0.9431
+- F1: 0.8115
+- Precision: 0.8659
+- Recall: 0.7636
+
+## 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: 9.946303722432942e-06
+- 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.6954        | 1.0   | 61   | 0.6728          | 0.6127   | 0.1189 | 0.0936    | 0.1629 |
+| 0.5462        | 2.0   | 122  | 0.3988          | 0.8683   | 0.4352 | 0.6972    | 0.3163 |
+| 0.3711        | 3.0   | 183  | 0.3401          | 0.8765   | 0.4703 | 0.7535    | 0.3419 |
+| 0.3269        | 4.0   | 244  | 0.3175          | 0.8883   | 0.4785 | 0.9524    | 0.3195 |
+| 0.2899        | 5.0   | 305  | 0.2781          | 0.9042   | 0.5961 | 0.92      | 0.4409 |
+| 0.2568        | 6.0   | 366  | 0.2576          | 0.9144   | 0.6745 | 0.865     | 0.5527 |
+| 0.2176        | 7.0   | 427  | 0.2305          | 0.9242   | 0.7376 | 0.8287    | 0.6645 |
+| 0.1879        | 8.0   | 488  | 0.2014          | 0.9329   | 0.7579 | 0.8991    | 0.6550 |
+| 0.1541        | 9.0   | 549  | 0.2002          | 0.9329   | 0.7842 | 0.8095    | 0.7604 |
+| 0.1275        | 10.0  | 610  | 0.1739          | 0.9431   | 0.8115 | 0.8659    | 0.7636 |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

added_tokens.json

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+{
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+}

config.json

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+{
+  "_name_or_path": "microsoft/deberta-v3-large",
+  "architectures": [
+    "DebertaV2ForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6",
+    "7": "LABEL_7"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6,
+    "LABEL_7": 7
+  },
+  "layer_norm_eps": 1e-07,
+  "max_position_embeddings": 512,
+  "max_relative_positions": -1,
+  "model_type": "deberta-v2",
+  "norm_rel_ebd": "layer_norm",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "pooler_dropout": 0,
+  "pooler_hidden_act": "gelu",
+  "pooler_hidden_size": 1024,
+  "pos_att_type": [
+    "p2c",
+    "c2p"
+  ],
+  "position_biased_input": false,
+  "position_buckets": 256,
+  "problem_type": "multi_label_classification",
+  "relative_attention": true,
+  "share_att_key": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.40.1",
+  "type_vocab_size": 0,
+  "vocab_size": 128100
+}

model.safetensors

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special_tokens_map.json

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+{
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+  "eos_token": "[SEP]",
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+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
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+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
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+}

spm.model

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tokenizer_config.json

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+  "bos_token": "[CLS]",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": false,
+  "eos_token": "[SEP]",
+  "mask_token": "[MASK]",
+  "max_length": 2056,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "sp_model_kwargs": {},
+  "split_by_punct": false,
+  "tokenizer_class": "DebertaV2Tokenizer",
+  "unk_token": "[UNK]",
+  "vocab_type": "spm"
+}

training_args.bin

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