End of training

README.md

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+---
+license: apache-2.0
+base_model: google-bert/bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: emotional-bert
+  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. -->
+
+# emotional-bert
+
+This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.5503
+- Accuracy: 0.4065
+- F1: 0.3831
+- Precision: 0.3926
+- Recall: 0.4065
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 2.82          | 1.0   | 270  | 2.7828          | 0.1733   | 0.1556 | 0.2256    | 0.1733 |
+| 1.4083        | 2.0   | 540  | 2.3254          | 0.3230   | 0.3235 | 0.3651    | 0.3230 |
+| 0.6017        | 3.0   | 810  | 2.1533          | 0.3766   | 0.3669 | 0.3880    | 0.3766 |
+| 0.2357        | 4.0   | 1080 | 2.2329          | 0.3721   | 0.3620 | 0.3727    | 0.3721 |
+| 0.0868        | 5.0   | 1350 | 2.3517          | 0.4065   | 0.3878 | 0.3897    | 0.4065 |
+| 0.0328        | 6.0   | 1620 | 2.5503          | 0.4065   | 0.3831 | 0.3926    | 0.4065 |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "google-bert/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": "serenity",
+    "1": "joy",
+    "10": "terror",
+    "11": "awe",
+    "12": "distraction",
+    "13": "surprise",
+    "14": "amazement",
+    "15": "disapproval",
+    "16": "pensiveness",
+    "17": "sadness",
+    "18": "grief",
+    "19": "remorse",
+    "2": "ecstasy",
+    "20": "boredom",
+    "21": "disgust",
+    "22": "loathing",
+    "23": "contempt",
+    "24": "annoyance",
+    "25": "anger",
+    "26": "rage",
+    "27": "aggressiveness",
+    "28": "interest",
+    "29": "anticipation",
+    "3": "love",
+    "30": "vigilance",
+    "31": "optimism",
+    "4": "acceptance",
+    "5": "trust",
+    "6": "admiration",
+    "7": "submission",
+    "8": "apprehension",
+    "9": "fear"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "acceptance": 4,
+    "admiration": 6,
+    "aggressiveness": 27,
+    "amazement": 14,
+    "anger": 25,
+    "annoyance": 24,
+    "anticipation": 29,
+    "apprehension": 8,
+    "awe": 11,
+    "boredom": 20,
+    "contempt": 23,
+    "disapproval": 15,
+    "disgust": 21,
+    "distraction": 12,
+    "ecstasy": 2,
+    "fear": 9,
+    "grief": 18,
+    "interest": 28,
+    "joy": 1,
+    "loathing": 22,
+    "love": 3,
+    "optimism": 31,
+    "pensiveness": 16,
+    "rage": 26,
+    "remorse": 19,
+    "sadness": 17,
+    "serenity": 0,
+    "submission": 7,
+    "surprise": 13,
+    "terror": 10,
+    "trust": 5,
+    "vigilance": 30
+  },
+  "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": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.39.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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runs/Apr11_07-07-29_ce3b1bc82a18/events.out.tfevents.1712819249.ce3b1bc82a18.581.0

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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,
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+      "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": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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