End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: roberta-wellness-classifier
+  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. -->
+
+# roberta-wellness-classifier
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.5355
+- Accuracy: 0.705
+- Auc: 0.898
+- Precision Class 0: 0.822
+- Precision Class 1: 0.81
+- Precision Class 2: 0.702
+- Precision Class 3: 0.644
+- Recall Class 0: 0.698
+- Recall Class 1: 0.63
+- Recall Class 2: 0.635
+- Recall Class 3: 0.776
+
+## 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: 3e-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 | Auc   | Precision Class 0 | Precision Class 1 | Precision Class 2 | Precision Class 3 | Recall Class 0 | Recall Class 1 | Recall Class 2 | Recall Class 3 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:-----------------:|:-----------------:|:-----------------:|:-----------------:|:--------------:|:--------------:|:--------------:|:--------------:|
+| 1.0739        | 1.0   | 70   | 0.7343          | 0.743    | 0.904 | 0.703             | 0.667             | 0.688             | 0.871             | 0.849          | 0.741          | 0.841          | 0.622          |
+| 0.7019        | 2.0   | 140  | 0.6927          | 0.722    | 0.917 | 0.764             | 0.867             | 0.736             | 0.678             | 0.792          | 0.481          | 0.619          | 0.816          |
+| 0.4696        | 3.0   | 210  | 0.7057          | 0.747    | 0.913 | 0.786             | 0.75              | 0.686             | 0.77              | 0.83           | 0.778          | 0.762          | 0.684          |
+| 0.3057        | 4.0   | 280  | 0.8772          | 0.78     | 0.906 | 0.843             | 0.933             | 0.674             | 0.826             | 0.811          | 0.519          | 0.952          | 0.724          |
+| 0.2182        | 5.0   | 350  | 0.8735          | 0.763    | 0.915 | 0.8               | 0.759             | 0.722             | 0.778             | 0.755          | 0.815          | 0.825          | 0.714          |
+| 0.1634        | 6.0   | 420  | 1.1820          | 0.714    | 0.901 | 0.783             | 0.762             | 0.714             | 0.676             | 0.679          | 0.593          | 0.714          | 0.765          |
+| 0.116         | 7.0   | 490  | 1.2979          | 0.73     | 0.897 | 0.788             | 0.731             | 0.737             | 0.698             | 0.774          | 0.704          | 0.667          | 0.755          |
+| 0.0844        | 8.0   | 560  | 1.4513          | 0.705    | 0.9   | 0.833             | 0.773             | 0.705             | 0.647             | 0.66           | 0.63           | 0.683          | 0.765          |
+| 0.0624        | 9.0   | 630  | 1.5216          | 0.71     | 0.901 | 0.826             | 0.783             | 0.702             | 0.652             | 0.717          | 0.667          | 0.635          | 0.765          |
+| 0.0446        | 10.0  | 700  | 1.5355          | 0.705    | 0.898 | 0.822             | 0.81              | 0.702             | 0.644             | 0.698          | 0.63           | 0.635          | 0.776          |
+
+
+### Framework versions
+
+- Transformers 4.45.1
+- Pytorch 2.4.0
+- Datasets 3.0.1
+- Tokenizers 0.20.0

config.json

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+{
+  "_name_or_path": "roberta-base",
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "PA",
+    "1": "IVA",
+    "2": "SA",
+    "3": "SEA"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "IVA": 1,
+    "PA": 0,
+    "SA": 2,
+    "SEA": 3
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.45.1",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

model.safetensors

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special_tokens_map.json

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+}

tokenizer_config.json

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+  "errors": "replace",
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+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "RobertaTokenizer",
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+}

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