End of training

README.md

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+---
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: fintunned-v2-roberta
+  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. -->
+
+# fintunned-v2-roberta
+
+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: 0.2012
+- Accuracy: 0.95
+- F1: 0.9504
+- Precision: 0.9517
+- Recall: 0.9498
+
+## 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: 5e-05
+- train_batch_size: 16
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 2.3929        | 0.45  | 50   | 2.2723          | 0.2773   | 0.1892 | 0.2335    | 0.2947 |
+| 1.2165        | 0.91  | 100  | 0.4612          | 0.8818   | 0.8839 | 0.8978    | 0.8825 |
+| 0.3732        | 1.36  | 150  | 0.3472          | 0.9045   | 0.9058 | 0.9092    | 0.9060 |
+| 0.3306        | 1.82  | 200  | 0.3077          | 0.9227   | 0.9249 | 0.9267    | 0.9250 |
+| 0.2537        | 2.27  | 250  | 0.2419          | 0.9273   | 0.9281 | 0.9290    | 0.9291 |
+| 0.0997        | 2.73  | 300  | 0.2012          | 0.95     | 0.9504 | 0.9517    | 0.9498 |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

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": "depression",
+    "1": "anxiety",
+    "2": "bipolar disorder",
+    "3": "schizophrenia",
+    "4": "PTSD",
+    "5": "OCD",
+    "6": "ADHD",
+    "7": "autism",
+    "8": "eating disorder",
+    "9": "personality disorder",
+    "10": "phobia"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "ADHD": 6,
+    "OCD": 5,
+    "PTSD": 4,
+    "anxiety": 1,
+    "autism": 7,
+    "bipolar disorder": 2,
+    "depression": 0,
+    "eating disorder": 8,
+    "personality disorder": 9,
+    "phobia": 10,
+    "schizophrenia": 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": "4.35.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

model.safetensors

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+oid sha256:dc1a386356db7df159da8720854b745b19cd60fef1163c6c0c8c686b51f2e636
+size 498640508

training_args.bin

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