End of training

README.md

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+---
+license: apache-2.0
+base_model: cm309/distilbert-base-uncased-finetuned-Financial-News-Superior
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: classification_bert_da_superior
+  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. -->
+
+# classification_bert_da_superior
+
+This model is a fine-tuned version of [cm309/distilbert-base-uncased-finetuned-Financial-News-Superior](https://huggingface.co/cm309/distilbert-base-uncased-finetuned-Financial-News-Superior) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3962
+- Accuracy: 0.8576
+- Precision: 0.8576
+- Recall: 0.8576
+- F1: 0.8568
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.5961        | 1.0   | 597  | 0.4288          | 0.8300   | 0.8336    | 0.8300 | 0.8312 |
+| 0.3723        | 2.0   | 1194 | 0.3962          | 0.8576   | 0.8576    | 0.8576 | 0.8568 |
+| 0.2497        | 3.0   | 1791 | 0.4695          | 0.8677   | 0.8668    | 0.8677 | 0.8665 |
+| 0.1816        | 4.0   | 2388 | 0.5746          | 0.8677   | 0.8677    | 0.8677 | 0.8676 |
+| 0.1281        | 5.0   | 2985 | 0.6205          | 0.8618   | 0.8610    | 0.8618 | 0.8612 |
+
+
+### Framework versions
+
+- Transformers 4.41.0
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "cm309/distilbert-base-uncased-finetuned-Financial-News-Superior",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2
+  },
+  "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": "4.41.0",
+  "vocab_size": 30522
+}

model.safetensors

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runs/May23_09-59-59_3357c1192e96/events.out.tfevents.1716458400.3357c1192e96.1531.0

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special_tokens_map.json

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+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
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+    "rstrip": false,
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+    "single_word": false
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+}

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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