End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+model-index:
+- name: bert-base-uncased-airlines-news-multi-label
+  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-base-uncased-airlines-news-multi-label
+
+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: 0.2807
+- F1: 0.7124
+- Roc Auc: 0.8100
+- Accuracy: 0.6766
+
+## 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: 7e-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
+- lr_scheduler_warmup_steps: 150
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
+| No log        | 1.0   | 118  | 0.2992          | 0.2412 | 0.5680  | 0.5234   |
+| No log        | 2.0   | 236  | 0.2628          | 0.5603 | 0.7177  | 0.6255   |
+| No log        | 3.0   | 354  | 0.2785          | 0.5691 | 0.7044  | 0.6426   |
+| No log        | 4.0   | 472  | 0.2674          | 0.6309 | 0.7619  | 0.6340   |
+| 0.2379        | 5.0   | 590  | 0.2640          | 0.6535 | 0.7768  | 0.6340   |
+| 0.2379        | 6.0   | 708  | 0.2929          | 0.6596 | 0.7683  | 0.6596   |
+| 0.2379        | 7.0   | 826  | 0.2778          | 0.7059 | 0.8189  | 0.6681   |
+| 0.2379        | 8.0   | 944  | 0.2807          | 0.7124 | 0.8100  | 0.6766   |
+| 0.0507        | 9.0   | 1062 | 0.3381          | 0.6688 | 0.7921  | 0.6511   |
+| 0.0507        | 10.0  | 1180 | 0.3160          | 0.6919 | 0.8259  | 0.6468   |
+| 0.0507        | 11.0  | 1298 | 0.3206          | 0.7063 | 0.8045  | 0.6936   |
+| 0.0507        | 12.0  | 1416 | 0.3273          | 0.6943 | 0.8060  | 0.6766   |
+| 0.0115        | 13.0  | 1534 | 0.3408          | 0.6794 | 0.7986  | 0.6638   |
+| 0.0115        | 14.0  | 1652 | 0.3488          | 0.6817 | 0.7971  | 0.6681   |
+| 0.0115        | 15.0  | 1770 | 0.3469          | 0.6962 | 0.8085  | 0.6766   |
+| 0.0115        | 16.0  | 1888 | 0.3517          | 0.6795 | 0.7966  | 0.6596   |
+| 0.0045        | 17.0  | 2006 | 0.3537          | 0.6814 | 0.8011  | 0.6596   |
+| 0.0045        | 18.0  | 2124 | 0.3566          | 0.6857 | 0.8021  | 0.6638   |
+| 0.0045        | 19.0  | 2242 | 0.3587          | 0.6795 | 0.7966  | 0.6596   |
+| 0.0045        | 20.0  | 2360 | 0.3596          | 0.6795 | 0.7966  | 0.6596   |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- 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": "capacity expansion",
+    "1": "market expansion",
+    "2": "merger & acquisition and finance investments",
+    "3": "outsourcing and alliance",
+    "4": "product introductions and improvements"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "capacity expansion": 0,
+    "market expansion": 1,
+    "merger & acquisition and finance investments": 2,
+    "outsourcing and alliance": 3,
+    "product introductions and improvements": 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": "4.41.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:bfe43e3cfbc7fec1ef24910f87e1afcf3053c31af1f09be5d313dabbd613bf04
+size 437967876

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
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "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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+size 5176