Saving model gmra_model_distilbert-base-uncased-distilled-squad_07112024T110436

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: distilbert-base-uncased-distilled-squad
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: gmra_model_distilbert-base-uncased-distilled-squad_07112024T110436
+  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. -->
+
+# gmra_model_distilbert-base-uncased-distilled-squad_07112024T110436
+
+This model is a fine-tuned version of [distilbert-base-uncased-distilled-squad](https://huggingface.co/distilbert-base-uncased-distilled-squad) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3023
+- Accuracy: 94.1125
+- F1: 0.9587
+
+## 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
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
+| No log        | 0.9982 | 142  | 0.3683          | 88.0492  | 0.7519 |
+| No log        | 1.9965 | 284  | 0.2634          | 91.5641  | 0.9238 |
+| No log        | 2.9947 | 426  | 0.2386          | 92.8822  | 0.9432 |
+| 0.3507        | 4.0    | 569  | 0.2321          | 93.9367  | 0.9579 |
+| 0.3507        | 4.9982 | 711  | 0.2897          | 93.4095  | 0.9536 |
+| 0.3507        | 5.9965 | 853  | 0.2745          | 94.2882  | 0.9606 |
+| 0.3507        | 6.9947 | 995  | 0.2892          | 94.3761  | 0.9616 |
+| 0.0379        | 8.0    | 1138 | 0.3055          | 94.0246  | 0.9579 |
+| 0.0379        | 8.9982 | 1280 | 0.3144          | 93.7610  | 0.9562 |
+| 0.0379        | 9.9824 | 1420 | 0.3023          | 94.1125  | 0.9587 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "distilbert-base-uncased-distilled-squad",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "change_request",
+    "1": "discussion_participation",
+    "2": "discussion_trigger",
+    "3": "acknowledgement",
+    "4": "reference",
+    "5": "critical"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "acknowledgement": 3,
+    "change_request": 0,
+    "critical": 5,
+    "discussion_participation": 1,
+    "discussion_trigger": 2,
+    "reference": 4
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "pad_token_id": 0,
+  "problem_type": "single_label_classification",
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.44.2",
+  "vocab_size": 30522
+}

model.safetensors

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runs/Nov07_05-34-36_d59182a992b8/events.out.tfevents.1730957693.d59182a992b8.262.0

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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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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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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": "DistilBertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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