ElliotWeiner/BERT Fine-Tuned Advisor Classifier 1

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+model-index:
+- name: bert-finetuned-advisor-feedback
+  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. -->
+
+# bert-finetuned-advisor-feedback
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0577
+- F1: 0.9377
+- Roc Auc: 0.9605
+- Accuracy: 0.8564
+
+## 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: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
+| No log        | 1.0   | 404  | 0.2224          | 0.4395 | 0.6424  | 0.0866   |
+| 0.2972        | 2.0   | 808  | 0.1361          | 0.8395 | 0.8720  | 0.5866   |
+| 0.1464        | 3.0   | 1212 | 0.0951          | 0.9056 | 0.9269  | 0.7599   |
+| 0.0841        | 4.0   | 1616 | 0.0770          | 0.9226 | 0.9472  | 0.8168   |
+| 0.0529        | 5.0   | 2020 | 0.0653          | 0.9344 | 0.9569  | 0.8540   |
+| 0.0529        | 6.0   | 2424 | 0.0603          | 0.9357 | 0.9565  | 0.8490   |
+| 0.0384        | 7.0   | 2828 | 0.0577          | 0.9377 | 0.9605  | 0.8564   |
+| 0.0323        | 8.0   | 3232 | 0.0569          | 0.9366 | 0.9579  | 0.8540   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.0
+- Tokenizers 0.19.1

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": "Communication_Positive",
+    "1": "Relationship_Positive",
+    "2": "Empathy_Positive",
+    "3": "Advocacy_Positive",
+    "4": "Resources_Positive",
+    "5": "AcademicSupport_Positive",
+    "6": "NonAcademic_Positive",
+    "7": "Communication_Negative",
+    "8": "Relationship_Negative",
+    "9": "Empathy_Negative",
+    "10": "Advocacy_Negative",
+    "11": "Resources_Negative",
+    "12": "AcademicSupport_Negative",
+    "13": "NonAcademic_Negative"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "AcademicSupport_Negative": 12,
+    "AcademicSupport_Positive": 5,
+    "Advocacy_Negative": 10,
+    "Advocacy_Positive": 3,
+    "Communication_Negative": 7,
+    "Communication_Positive": 0,
+    "Empathy_Negative": 9,
+    "Empathy_Positive": 2,
+    "NonAcademic_Negative": 13,
+    "NonAcademic_Positive": 6,
+    "Relationship_Negative": 8,
+    "Relationship_Positive": 1,
+    "Resources_Negative": 11,
+    "Resources_Positive": 4
+  },
+  "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": "4.44.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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runs/Sep23_17-31-42_2b5c4dfc1497/events.out.tfevents.1727112783.2b5c4dfc1497.3546.0

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special_tokens_map.json

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

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
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+      "lstrip": false,
+      "normalized": false,
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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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