rajuEEE/ExampleBert

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- sem_eval_2018_task_1
+metrics:
+- f1
+- accuracy
+model-index:
+- name: bert-finetuned-sem_eval-english
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: sem_eval_2018_task_1
+      type: sem_eval_2018_task_1
+      config: subtask5.english
+      split: validation
+      args: subtask5.english
+    metrics:
+    - name: F1
+      type: f1
+      value: 0.659666128163705
+    - name: Accuracy
+      type: accuracy
+      value: 0.24943566591422123
+---
+
+<!-- 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. -->
+
+# bert-finetuned-sem_eval-english
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the sem_eval_2018_task_1 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3267
+- F1: 0.6597
+- Roc Auc: 0.7618
+- Accuracy: 0.2494
+
+## 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: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
+| 0.406         | 1.0   | 855  | 0.3267          | 0.6597 | 0.7618  | 0.2494   |
+
+
+### Framework versions
+
+- Transformers 4.32.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "bert-base-uncased",
+  "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,
+  "id2label": {
+    "0": "anger",
+    "1": "anticipation",
+    "2": "disgust",
+    "3": "fear",
+    "4": "joy",
+    "5": "love",
+    "6": "optimism",
+    "7": "pessimism",
+    "8": "sadness",
+    "9": "surprise",
+    "10": "trust"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "anger": 0,
+    "anticipation": 1,
+    "disgust": 2,
+    "fear": 3,
+    "joy": 4,
+    "love": 5,
+    "optimism": 6,
+    "pessimism": 7,
+    "sadness": 8,
+    "surprise": 9,
+    "trust": 10
+  },
+  "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": "multi_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.32.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
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+size 438031153

special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "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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